Stephan Günnemann
Technical University of Munich, Germany
Carnegie Mellon University, Pittsburgh, USA
http://www.kdd.in.tum.de/en/home/
http://www.cs.cmu.edu/~sguennem/
https://scholar.google.com/citations?user=npqoAWwAAAAJ
https://dl.acm.org/profile/81447604694
https://orcid.org/0000-0001-7772-5059
Leo Schwinn
David Dobre
Sophie Xhonneux
Gauthier Gidel
Stephan Günnemann
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space.
2024
abs/2402.09063
CoRR
https://doi.org/10.48550/arXiv.2402.09063
db/journals/corr/corr2402.html#abs-2402-09063
Simon Geisler
Tom Wollschläger
M. H. I. Abdalla
Johannes Gasteiger
Stephan Günnemann
Attacking Large Language Models with Projected Gradient Descent.
2024
abs/2402.09154
CoRR
https://doi.org/10.48550/arXiv.2402.09154
db/journals/corr/corr2402.html#abs-2402-09154
Rayen Dhahri
Alexander Immer
Bertrand Charpentier
Stephan Günnemann
Vincent Fortuin
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks Using the Marginal Likelihood.
2024
abs/2402.15978
CoRR
https://doi.org/10.48550/arXiv.2402.15978
db/journals/corr/corr2402.html#abs-2402-15978
Richard Leibrandt
Stephan Günnemann
Generalized density attractor clustering for incomplete data.
970-1009
2023
March
37
Data Min. Knowl. Discov.
2
https://doi.org/10.1007/s10618-022-00904-6
db/journals/datamine/datamine37.html#LeibrandtG23
Hao Lin 0002
Hongfu Liu 0001
Junjie Wu 0002
Hong Li
Stephan Günnemann
Algorithm 1038: KCC: A MATLAB Package for k-Means-based Consensus Clustering.
40:1-40:27
2023
December
49
ACM Trans. Math. Softw.
4
https://doi.org/10.1145/3616011
db/journals/toms/toms49.html#LinLWLG23
Nicola Franco
Daniel Korth
Jeanette Miriam Lorenz
Karsten Roscher
Stephan Günnemann
Diffusion Denoised Smoothing for Certified and Adversarial Robust Out Of Distribution.
2023
AISafety/SafeRL@IJCAI
https://ceur-ws.org/Vol-3505/paper_5.pdf
conf/aisafety/2023
db/conf/aisafety/aisafety2023.html#FrancoKLRG23
Tom Haider
Karsten Roscher
Felippe Schmoeller da Roza
Stephan Günnemann
Out-of-Distribution Detection for Reinforcement Learning Agents with Probabilistic Dynamics Models.
851-859
2023
AAMAS
https://dl.acm.org/doi/10.5555/3545946.3598721
conf/atal/2023
db/conf/atal/aamas2023.html#HaiderRRG23
Sebastian Schmidt 0006
Stephan Günnemann
Stream-based Active Learning by Exploiting Temporal Properties in Perception with Temporal Predicted Loss.
664
2023
BMVC
http://proceedings.bmvc2023.org/664/
conf/bmvc/2023
db/conf/bmvc/bmvc2023.html#SchmidtG23
Armin Moin
Atta Badii
Stephan Günnemann
Moharram Challenger
Enabling Machine Learning in Software Architecture Frameworks.
92-93
2023
CAIN
https://doi.org/10.1109/CAIN58948.2023.00021
conf/cain/2023
db/conf/cain/cain2023.html#MoinBGC23
Jianxiang Feng
Jongseok Lee
Simon Geisler
Stephan Günnemann
Rudolph Triebel
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning.
3214-3241
2023
CoRL
https://proceedings.mlr.press/v229/feng23b.html
conf/corl/2023
db/conf/corl/corl2023.html#FengLGGT23
Nicholas Gao
Stephan Günnemann
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks.
2023
ICLR
https://openreview.net/pdf?id=Tuk3Pqaizx
conf/iclr/2023
db/conf/iclr/iclr2023.html#GaoG23
Lukas Gosch
Daniel Sturm 0002
Simon Geisler
Stephan Günnemann
Revisiting Robustness in Graph Machine Learning.
2023
ICLR
https://openreview.net/pdf?id=h1o7Ry9Zctm
conf/iclr/2023
db/conf/iclr/iclr2023.html#Gosch0GG23
Raffaele Paolino
Aleksandar Bojchevski
Stephan Günnemann
Gitta Kutyniok
Ron Levie
Unveiling the sampling density in non-uniform geometric graphs.
2023
ICLR
https://openreview.net/pdf?id=mnVf1W6ipGm
conf/iclr/2023
db/conf/iclr/iclr2023.html#PaolinoBGKL23
Jan Schuchardt
Tom Wollschläger
Aleksandar Bojchevski
Stephan Günnemann
Localized Randomized Smoothing for Collective Robustness Certification.
2023
ICLR
https://openreview.net/pdf?id=-k7Lvk0GpBl
conf/iclr/2023
db/conf/iclr/iclr2023.html#SchuchardtWBG23
Marin Bilos
Kashif Rasul
Anderson Schneider
Yuriy Nevmyvaka
Stephan Günnemann
Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion.
2452-2470
2023
ICML
https://proceedings.mlr.press/v202/bilos23a.html
conf/icml/2023
db/conf/icml/icml2023.html#BilosRSNG23
Nicholas Gao
Stephan Günnemann
Generalizing Neural Wave Functions.
10708-10726
2023
ICML
https://proceedings.mlr.press/v202/gao23c.html
conf/icml/2023
db/conf/icml/icml2023.html#GaoG23
Simon Geisler
Yujia Li
Daniel J. Mankowitz
Ali Taylan Cemgil
Stephan Günnemann
Cosmin Paduraru
Transformers Meet Directed Graphs.
11144-11172
2023
ICML
https://proceedings.mlr.press/v202/geisler23a.html
conf/icml/2023
db/conf/icml/icml2023.html#GeislerLMCGP23
Arthur Kosmala
Johannes Gasteiger
Nicholas Gao
Stephan Günnemann
Ewald-based Long-Range Message Passing for Molecular Graphs.
17544-17563
2023
ICML
https://proceedings.mlr.press/v202/kosmala23a.html
conf/icml/2023
db/conf/icml/icml2023.html#KosmalaGGG23
Tom Wollschläger
Nicholas Gao
Bertrand Charpentier
Mohamed Amine Ketata
Stephan Günnemann
Uncertainty Estimation for Molecules: Desiderata and Methods.
37133-37156
2023
ICML
https://proceedings.mlr.press/v202/wollschlager23a.html
conf/icml/2023
db/conf/icml/icml2023.html#WollschlagerGCK23
Franziska Schwaiger
Andrea Matic
Karsten Roscher
Stephan Günnemann
Preventing Errors in Person Detection: A Part-Based Self-Monitoring Framework.
1-8
2023
IV
https://doi.org/10.1109/IV55152.2023.10186644
conf/ivs/2023
db/conf/ivs/ivs2023.html#SchwaigerMRG23
Lukas Gosch
Simon Geisler
Daniel Sturm 0002
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions.
2023
NeurIPS
http://papers.nips.cc/paper_files/paper/2023/hash/b5a801e6bc4f4ffa3e6786518a324488-Abstract-Conference.html
conf/nips/2023
db/conf/nips/neurips2023.html#GoschG0CZG23
David Lüdke
Marin Bilos
Oleksandr Shchur
Marten Lienen
Stephan Günnemann
Add and Thin: Diffusion for Temporal Point Processes.
2023
NeurIPS
http://papers.nips.cc/paper_files/paper/2023/hash/b1d9c7e7bd265d81aae8d74a7a6bd7f1-Abstract-Conference.html
conf/nips/2023
db/conf/nips/neurips2023.html#LudkeBSLG23
Yan Scholten
Jan Schuchardt
Aleksandar Bojchevski
Stephan Günnemann
Hierarchical Randomized Smoothing.
2023
NeurIPS
http://papers.nips.cc/paper_files/paper/2023/hash/9c0efc0d84c263972af72bf70a2de533-Abstract-Conference.html
conf/nips/2023
db/conf/nips/neurips2023.html#ScholtenSBG23
Jan Schuchardt
Yan Scholten
Stephan Günnemann
(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More.
2023
NeurIPS
http://papers.nips.cc/paper_files/paper/2023/hash/00db17c36b5435195760520efa96d99c-Abstract-Conference.html
conf/nips/2023
db/conf/nips/neurips2023.html#SchuchardtSG23
Jonas Gregor Wiese
Lisa Wimmer
Theodore Papamarkou
Bernd Bischl
Stephan Günnemann
David Rügamer
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry.
459-474
2023
ECML/PKDD (1)
https://doi.org/10.1007/978-3-031-43412-9_27
conf/pkdd/2023-1
db/conf/pkdd/pkdd2023-1.html#WieseWPBGR23
Nicola Franco
Tom Wollschläger
Benedikt Poggel
Stephan Günnemann
Jeanette Miriam Lorenz
Efficient MILP Decomposition in Quantum Computing for ReLU Network Robustness.
524-534
2023
QCE
https://doi.org/10.1109/QCE57702.2023.00066
conf/qce/2023
db/conf/qce/qce2023.html#FrancoWPGL23
Morgane Ayle
Jan Schuchardt
Lukas Gosch
Daniel Zügner
Stephan Günnemann
Training Differentially Private Graph Neural Networks with Random Walk Sampling.
2023
abs/2301.00738
CoRR
https://doi.org/10.48550/arXiv.2301.00738
db/journals/corr/corr2301.html#abs-2301-00738
Yan Scholten
Jan Schuchardt
Simon Geisler
Aleksandar Bojchevski
Stephan Günnemann
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks.
2023
abs/2301.02039
CoRR
https://doi.org/10.48550/arXiv.2301.02039
db/journals/corr/corr2301.html#abs-2301-02039
Felix Mujkanovic
Simon Geisler
Stephan Günnemann
Aleksandar Bojchevski
Are Defenses for Graph Neural Networks Robust?
2023
abs/2301.13694
CoRR
https://doi.org/10.48550/arXiv.2301.13694
db/journals/corr/corr2301.html#abs-2301-13694
Simon Geisler
Yujia Li
Daniel J. Mankowitz
Ali Taylan Cemgil
Stephan Günnemann
Cosmin Paduraru
Transformers Meet Directed Graphs.
2023
abs/2302.00049
CoRR
https://doi.org/10.48550/arXiv.2302.00049
db/journals/corr/corr2302.html#abs-2302-00049
Jan Schuchardt
Aleksandar Bojchevski
Johannes Gasteiger
Stephan Günnemann
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks.
2023
abs/2302.02829
CoRR
https://doi.org/10.48550/arXiv.2302.02829
db/journals/corr/corr2302.html#abs-2302-02829
Nicholas Gao
Stephan Günnemann
Generalizing Neural Wave Functions.
2023
abs/2302.04168
CoRR
https://doi.org/10.48550/arXiv.2302.04168
db/journals/corr/corr2302.html#abs-2302-04168
Arthur Kosmala
Johannes Gasteiger
Nicholas Gao
Stephan Günnemann
Ewald-based Long-Range Message Passing for Molecular Graphs.
2023
abs/2303.04791
CoRR
https://doi.org/10.48550/arXiv.2303.04791
db/journals/corr/corr2303.html#abs-2303-04791
Bertrand Charpentier
Chenxiang Zhang
Stephan Günnemann
Training, Architecture, and Prior for Deterministic Uncertainty Methods.
2023
abs/2303.05796
CoRR
https://doi.org/10.48550/arXiv.2303.05796
db/journals/corr/corr2303.html#abs-2303-05796
Nicola Franco
Daniel Korth
Jeanette Miriam Lorenz
Karsten Roscher
Stephan Günnemann
Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection.
2023
abs/2303.14961
CoRR
https://doi.org/10.48550/arXiv.2303.14961
db/journals/corr/corr2303.html#abs-2303-14961
Johannes Getzner
Bertrand Charpentier
Stephan Günnemann
Accuracy is not the only Metric that matters: Estimating the Energy Consumption of Deep Learning Models.
2023
abs/2304.00897
CoRR
https://doi.org/10.48550/arXiv.2304.00897
db/journals/corr/corr2304.html#abs-2304-00897
Jonas Gregor Wiese
Lisa Wimmer
Theodore Papamarkou
Bernd Bischl
Stephan Günnemann
David Rügamer
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry.
2023
abs/2304.02902
CoRR
https://doi.org/10.48550/arXiv.2304.02902
db/journals/corr/corr2304.html#abs-2304-02902
Nicola Franco
Tom Wollschläger
Benedikt Poggel
Stephan Günnemann
Jeanette Miriam Lorenz
Efficient MILP Decomposition in Quantum Computing for ReLU Network Robustness.
2023
abs/2305.00472
CoRR
https://doi.org/10.48550/arXiv.2305.00472
db/journals/corr/corr2305.html#abs-2305-00472
Lukas Gosch
Daniel Sturm 0002
Simon Geisler
Stephan Günnemann
Revisiting Robustness in Graph Machine Learning.
2023
abs/2305.00851
CoRR
https://doi.org/10.48550/arXiv.2305.00851
db/journals/corr/corr2305.html#abs-2305-00851
Emanuele Rossi
Bertrand Charpentier
Francesco Di Giovanni
Fabrizio Frasca
Stephan Günnemann
Michael M. Bronstein
Edge Directionality Improves Learning on Heterophilic Graphs.
2023
abs/2305.10498
CoRR
https://doi.org/10.48550/arXiv.2305.10498
db/journals/corr/corr2305.html#abs-2305-10498
Leon Hetzel
Johanna Sommer
Bastian Rieck
Fabian J. Theis
Stephan Günnemann
MAGNet: Motif-Agnostic Generation of Molecules from Shapes.
2023
abs/2305.19303
CoRR
https://doi.org/10.48550/arXiv.2305.19303
db/journals/corr/corr2305.html#abs-2305-19303
Marten Lienen
Jan Hansen-Palmus
David Lüdke
Stephan Günnemann
Generative Diffusion for 3D Turbulent Flows.
2023
abs/2306.01776
CoRR
https://doi.org/10.48550/arXiv.2306.01776
db/journals/corr/corr2306.html#abs-2306-01776
Tom Wollschläger
Nicholas Gao
Bertrand Charpentier
Mohamed Amine Ketata
Stephan Günnemann
Uncertainty Estimation for Molecules: Desiderata and Methods.
2023
abs/2306.14916
CoRR
https://doi.org/10.48550/arXiv.2306.14916
db/journals/corr/corr2306.html#abs-2306-14916
Lukas Gosch
Simon Geisler
Daniel Sturm 0002
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
Adversarial Training for Graph Neural Networks.
2023
abs/2306.15427
CoRR
https://doi.org/10.48550/arXiv.2306.15427
db/journals/corr/corr2306.html#abs-2306-15427
Johanna Sommer
Leon Hetzel
David Lüdke
Fabian J. Theis
Stephan Günnemann
The power of motifs as inductive bias for learning molecular distributions.
2023
abs/2306.17246
CoRR
https://doi.org/10.48550/arXiv.2306.17246
db/journals/corr/corr2306.html#abs-2306-17246
Jianxiang Feng
Matan Atad
Ismael Rodríguez
Maximilian Durner
Stephan Günnemann
Rudolph Triebel
Density-based Feasibility Learning with Normalizing Flows for Introspective Robotic Assembly.
2023
abs/2307.01317
CoRR
https://doi.org/10.48550/arXiv.2307.01317
db/journals/corr/corr2307.html#abs-2307-01317
Franziska Schwaiger
Andrea Matic
Karsten Roscher
Stephan Günnemann
Preventing Errors in Person Detection: A Part-Based Self-Monitoring Framework.
2023
abs/2307.04533
CoRR
https://doi.org/10.48550/arXiv.2307.04533
db/journals/corr/corr2307.html#abs-2307-04533
Xuan Zhang
Limei Wang
Jacob Helwig
Youzhi Luo
Cong Fu 0003
Yaochen Xie
Meng Liu
Yuchao Lin
Zhao Xu 0005
Keqiang Yan
Keir Adams
Maurice Weiler
Xiner Li
Tianfan Fu
Yucheng Wang
Haiyang Yu
Yuqing Xie 0006
Xiang Fu 0005
Alex Strasser
Shenglong Xu
Yi Liu 0059
Yuanqi Du
Alexandra Saxton
Hongyi Ling
Hannah Lawrence
Hannes Stärk
Shurui Gui
Carl Edwards
Nicholas Gao
Adriana Ladera
Tailin Wu
Elyssa F. Hofgard
Aria Mansouri Tehrani
Rui Wang 0086
Ameya Daigavane
Montgomery Bohde
Jerry Kurtin
Qian Huang
Tuong Phung
Minkai Xu
Chaitanya K. Joshi
Simon V. Mathis
Kamyar Azizzadenesheli
Ada Fang
Alán Aspuru-Guzik
Erik J. Bekkers
Michael M. Bronstein
Marinka Zitnik
Anima Anandkumar
Stefano Ermon
Pietro Liò
Rose Yu
Stephan Günnemann
Jure Leskovec
Heng Ji
Jimeng Sun 0001
Regina Barzilay
Tommi S. Jaakkola
Connor W. Coley
Xiaoning Qian
Xiaofeng Qian
Tess E. Smidt
Shuiwang Ji
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
2023
abs/2307.08423
CoRR
https://doi.org/10.48550/arXiv.2307.08423
db/journals/corr/corr2307.html#abs-2307-08423
Armin Moin
Atta Badii
Stephan Günnemann
Moharram Challenger
AI-Enabled Software and System Architecture Frameworks: Focusing on smart Cyber-Physical Systems (CPS).
2023
abs/2308.05239
CoRR
https://doi.org/10.48550/arXiv.2308.05239
db/journals/corr/corr2308.html#abs-2308-05239
Francesco Campi
Lukas Gosch
Tom Wollschläger
Yan Scholten
Stephan Günnemann
Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness.
2023
abs/2308.08173
CoRR
https://doi.org/10.48550/arXiv.2308.08173
db/journals/corr/corr2308.html#abs-2308-08173
Sebastian Schmidt 0006
Stephan Günnemann
Stream-based Active Learning by Exploiting Temporal Properties in Perception with Temporal Predicted Loss.
2023
abs/2309.05517
CoRR
https://doi.org/10.48550/arXiv.2309.05517
db/journals/corr/corr2309.html#abs-2309-05517
Marcel Kollovieh
Lukas Gosch
Yan Scholten
Marten Lienen
Stephan Günnemann
Assessing Robustness via Score-Based Adversarial Image Generation.
2023
abs/2310.04285
CoRR
https://doi.org/10.48550/arXiv.2310.04285
db/journals/corr/corr2310.html#abs-2310-04285
Yan Scholten
Jan Schuchardt
Aleksandar Bojchevski
Stephan Günnemann
Hierarchical Randomized Smoothing.
2023
abs/2310.16221
CoRR
https://doi.org/10.48550/arXiv.2310.16221
db/journals/corr/corr2310.html#abs-2310-16221
Leo Schwinn
David Dobre
Stephan Günnemann
Gauthier Gidel
Adversarial Attacks and Defenses in Large Language Models: Old and New Threats.
2023
abs/2310.19737
CoRR
https://doi.org/10.48550/arXiv.2310.19737
db/journals/corr/corr2310.html#abs-2310-19737
David Lüdke
Marin Bilos
Oleksandr Shchur
Marten Lienen
Stephan Günnemann
Add and Thin: Diffusion for Temporal Point Processes.
2023
abs/2311.01139
CoRR
https://doi.org/10.48550/arXiv.2311.01139
db/journals/corr/corr2311.html#abs-2311-01139
Jianxiang Feng
Jongseok Lee
Simon Geisler
Stephan Günnemann
Rudolph Triebel
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning.
2023
abs/2311.06481
CoRR
https://doi.org/10.48550/arXiv.2311.06481
db/journals/corr/corr2311.html#abs-2311-06481
Filippo Guerranti
Zinuo Yi
Anna Starovoit
Rafiq Kamel
Simon Geisler
Stephan Günnemann
On the Adversarial Robustness of Graph Contrastive Learning Methods.
2023
abs/2311.17853
CoRR
https://doi.org/10.48550/arXiv.2311.17853
db/journals/corr/corr2311.html#abs-2311-17853
Jan Schuchardt
Yan Scholten
Stephan Günnemann
(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More.
2023
abs/2312.02708
CoRR
https://doi.org/10.48550/arXiv.2312.02708
db/journals/corr/corr2312.html#abs-2312-02708
Michael Plainer
Hannes Stärk
Charlotte Bunne
Stephan Günnemann
Transition Path Sampling with Boltzmann Generator-based MCMC Moves.
2023
abs/2312.05340
CoRR
https://doi.org/10.48550/arXiv.2312.05340
db/journals/corr/corr2312.html#abs-2312-05340
Ege Erdogan
Simon Geisler
Stephan Günnemann
Poisoning × Evasion: Symbiotic Adversarial Robustness for Graph Neural Networks.
2023
abs/2312.05502
CoRR
https://doi.org/10.48550/arXiv.2312.05502
db/journals/corr/corr2312.html#abs-2312-05502
Artur Mrowca
Florian Gyrock
Stephan Günnemann
Temporal state change Bayesian networks for modeling of evolving multivariate state sequences: model, structure discovery and parameter estimation.
240-294
2022
36
Data Min. Knowl. Discov.
1
https://doi.org/10.1007/s10618-021-00807-y
db/journals/datamine/datamine36.html#MrowcaGG22
Maximilian E. Schüle
Harald Lang
Maximilian Springer
Alfons Kemper
Thomas Neumann 0001
Stephan Günnemann
Recursive SQL and GPU-support for in-database machine learning.
205-259
2022
40
Distributed Parallel Databases
2-3
https://doi.org/10.1007/s10619-022-07417-7
db/journals/dpd/dpd40.html#SchuleLSKNG22
Aleksei Kuvshinov
Stephan Günnemann
Robustness verification of ReLU networks via quadratic programming.
2407-2433
2022
111
Mach. Learn.
7
https://doi.org/10.1007/s10994-022-06132-9
db/journals/ml/ml111.html#KuvshinovG22
Sina Stocker
Johannes Gasteiger
Florian Becker
Stephan Günnemann
Johannes T. Margraf
How robust are modern graph neural network potentials in long and hot molecular dynamics simulations?
45010
2022
December
3
Mach. Learn. Sci. Technol.
4
https://doi.org/10.1088/2632-2153/ac9955
https://www.wikidata.org/entity/Q114939707
db/journals/mlst/mlst3.html#StockerGBGM22
Armin Moin
Moharram Challenger
Atta Badii
Stephan Günnemann
A model-driven approach to machine learning and software modeling for the IoT.
987-1014
2022
21
Softw. Syst. Model.
3
https://doi.org/10.1007/s10270-021-00967-x
https://www.wikidata.org/entity/Q114389497
db/journals/sosym/sosym21.html#MoinCBG22
Johannes Gasteiger
Muhammed Shuaibi
Anuroop Sriram
Stephan Günnemann
Zachary W. Ulissi
C. Lawrence Zitnick
Abhishek Das
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets.
2022
2022
Trans. Mach. Learn. Res.
https://openreview.net/forum?id=u8tvSxm4Bs
db/journals/tmlr/tmlr2022.html#GasteigerSSGUZD22
Kevin Kennard Thiel
Florian Naumann
Eduard Jundt
Stephan Günnemann
Gudrun Klinker
C.DOT - Convolutional Deep Object Tracker for Augmented Reality Based Purely on Synthetic Data.
4434-4451
2022
28
IEEE Trans. Vis. Comput. Graph.
12
https://doi.org/10.1109/TVCG.2021.3089096
db/journals/tvcg/tvcg28.html#ThielNJGK22
Aleksei Kuvshinov
Daniel Knobloch
Daniel Külzer
Elen Vardanyan
Stephan Günnemann
Domain Reconstruction for UWB Car Key Localization Using Generative Adversarial Networks.
12552-12558
2022
AAAI
https://doi.org/10.1609/aaai.v36i11.21526
conf/aaai/2022
db/conf/aaai/aaai2022.html#KuvshinovKKVG22
Poulami Sinhamahapatra
Rajat Koner
Karsten Roscher
Stephan Günnemann
Is it all a cluster game? - Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space.
2022
SafeAI@AAAI
https://ceur-ws.org/Vol-3087/paper_29.pdf
conf/aaai/2022safeai
db/conf/aaai/safeai2022.html#SinhamahapatraK22
Armin Moin
Moharram Challenger
Atta Badii
Stephan Günnemann
Supporting AI Engineering on the IoT Edge through Model-Driven TinyML.
884-893
2022
COMPSAC
https://doi.org/10.1109/COMPSAC54236.2022.00140
conf/compsac/2022
db/conf/compsac/compsac2022.html#MoinCBG22
Codrut-Andrei Diaconu
Sudipan Saha
Stephan Günnemann
Xiao Xiang Zhu 0001
Understanding the Role of Weather Data for Earth Surface Forecasting using a ConvLSTM-based Model.
1361-1370
2022
CVPR Workshops
https://doi.org/10.1109/CVPRW56347.2022.00142
conf/cvpr/2022w
db/conf/cvpr/cvpr2022w.html#DiaconuSGZ22
Armin Moin
Moharram Challenger
Atta Badii
Stephan Günnemann
Towards Model-Driven Engineering for Quantum AI.
1121-1131
2022
GI-Jahrestagung
https://doi.org/10.18420/inf2022_95
conf/gi/2022
db/conf/gi/gi2022.html#MoinCBG22
Bertrand Charpentier
Oliver Borchert
Daniel Zügner
Simon Geisler
Stephan Günnemann
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions.
2022
ICLR
https://openreview.net/forum?id=tV3N0DWMxCg
conf/iclr/2022
db/conf/iclr/iclr2022.html#CharpentierBZGG22
Bertrand Charpentier
Simon Kibler
Stephan Günnemann
Differentiable DAG Sampling.
2022
ICLR
https://openreview.net/forum?id=9wOQOgNe-w
conf/iclr/2022
db/conf/iclr/iclr2022.html#CharpentierKG22
Nicholas Gao
Stephan Günnemann
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions.
2022
ICLR
https://openreview.net/forum?id=apv504XsysP
conf/iclr/2022
db/conf/iclr/iclr2022.html#GaoG22
Simon Geisler
Johanna Sommer
Jan Schuchardt
Aleksandar Bojchevski
Stephan Günnemann
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness.
2022
ICLR
https://openreview.net/forum?id=vJZ7dPIjip3
conf/iclr/2022
db/conf/iclr/iclr2022.html#GeislerSSBG22
Marten Lienen
Stephan Günnemann
Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks.
2022
ICLR
https://openreview.net/forum?id=HFmAukZ-k-2
conf/iclr/2022
db/conf/iclr/iclr2022.html#LienenG22
Daniel Zügner
Bertrand Charpentier
Morgane Ayle
Sascha Geringer
Stephan Günnemann
End-to-End Learning of Probabilistic Hierarchies on Graphs.
2022
ICLR
https://openreview.net/forum?id=g2LCQwG7Of
conf/iclr/2022
db/conf/iclr/iclr2022.html#ZugnerCAGG22
John Rachwan
Daniel Zügner
Bertrand Charpentier
Simon Geisler
Morgane Ayle
Stephan Günnemann
Winning the Lottery Ahead of Time: Efficient Early Network Pruning.
18293-18309
2022
ICML
https://proceedings.mlr.press/v162/rachwan22a.html
conf/icml/2022
db/conf/icml/icml2022.html#RachwanZCGAG22
Hannes Stärk
Dominique Beaini
Gabriele Corso
Prudencio Tossou
Christian Dallago
Stephan Günnemann
Pietro Lió
3D Infomax improves GNNs for Molecular Property Prediction.
20479-20502
2022
ICML
https://proceedings.mlr.press/v162/stark22a.html
conf/icml/2022
db/conf/icml/icml2022.html#StarkBCTDGL22
Peter Súkeník
Aleksei Kuvshinov
Stephan Günnemann
Intriguing Properties of Input-Dependent Randomized Smoothing.
20697-20743
2022
ICML
https://proceedings.mlr.press/v162/sukeni-k22a.html
conf/icml/2022
db/conf/icml/icml2022.html#SukenikKG22
Felippe Schmoeller Roza
Hassan Rasheed
Karsten Roscher
Xiangyu Ning
Stephan Günnemann
Safe Robot Navigation Using Constrained Hierarchical Reinforcement Learning.
737-742
2022
ICMLA
https://doi.org/10.1109/ICMLA55696.2022.00123
conf/icmla/2022
db/conf/icmla/icmla2022.html#RozaRRNG22
Armin Moin
Andrei Mituca
Moharram Challenger
Atta Badii
Stephan Günnemann
ML-Quadrat & DriotData: A Model-Driven Engineering Tool and a Low-Code Platform for Smart IoT Services.
144-148
2022
ICSE-Companion
https://doi.org/10.1145/3510454.3516841
https://doi.org/10.1109/ICSE-Companion55297.2022.9793752
conf/icse/2022c
db/conf/icse/icse2022c.html#MoinMCBG22
Johannes Gasteiger
Chendi Qian
Stephan Günnemann
Influence-Based Mini-Batching for Graph Neural Networks.
9
2022
LoG
https://proceedings.mlr.press/v198/gasteiger22a.html
conf/log/2022
db/conf/log/log2022.html#GasteigerQG22
Alexandru Cristian Mara
Jefrey Lijffijt
Stephan Günnemann
Tijl De Bie
A Systematic Evaluation of Node Embedding Robustness.
42
2022
LoG
https://proceedings.mlr.press/v198/mara22a.html
conf/log/2022
db/conf/log/log2022.html#MaraLGB22
Jörg Christian Kirchhof
Evgeny Kusmenko
Jonas Ritz
Bernhard Rumpe
Armin Moin
Atta Badii
Stephan Günnemann
Moharram Challenger
MDE for machine learning-enabled software systems: a case study and comparison of MontiAnna & ML-Quadrat.
380-387
2022
MoDELS (Companion)
https://doi.org/10.1145/3550356.3561576
conf/models/2022c
db/conf/models/models2022c.html#KirchhofKRRMBGC22
Leon Hetzel
Simon Böhm
Niki Kilbertus
Stephan Günnemann
Mohammad Lotfollahi
Fabian J. Theis
Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution.
2022
conf/nips/2022
NeurIPS
http://papers.nips.cc/paper_files/paper/2022/hash/aa933b5abc1be30baece1d230ec575a7-Abstract-Conference.html
db/conf/nips/neurips2022.html#HetzelBKGLT22
Felix Mujkanovic
Simon Geisler
Stephan Günnemann
Aleksandar Bojchevski
Are Defenses for Graph Neural Networks Robust?
2022
conf/nips/2022
NeurIPS
http://papers.nips.cc/paper_files/paper/2022/hash/3ac904a31f9141444009777abef2ed8e-Abstract-Conference.html
db/conf/nips/neurips2022.html#MujkanovicGGB22
Yan Scholten
Jan Schuchardt
Simon Geisler
Aleksandar Bojchevski
Stephan Günnemann
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks.
2022
conf/nips/2022
NeurIPS
http://papers.nips.cc/paper_files/paper/2022/hash/d66d8164cfbf012cac2866edbb375035-Abstract-Conference.html
db/conf/nips/neurips2022.html#ScholtenSGBG22
Jan Schuchardt
Stephan Günnemann
Invariance-Aware Randomized Smoothing Certificates.
2022
conf/nips/2022
NeurIPS
http://papers.nips.cc/paper_files/paper/2022/hash/ddd45979547a35db2471e69cbf3bca54-Abstract-Conference.html
db/conf/nips/neurips2022.html#SchuchardtG22
Nicola Franco
Tom Wollschläger
Nicholas Gao
Jeanette Miriam Lorenz
Stephan Günnemann
Quantum Robustness Verification: A Hybrid Quantum-Classical Neural Network Certification Algorithm.
142-153
2022
QCE
https://doi.org/10.1109/QCE53715.2022.00033
conf/qce/2022
db/conf/qce/qce2022.html#FrancoWGLG22
Oliver Borchert
David Salinas
Valentin Flunkert
Tim Januschowski
Stephan Günnemann
Multi-Objective Model Selection for Time Series Forecasting.
2022
abs/2202.08485
CoRR
https://arxiv.org/abs/2202.08485
db/journals/corr/corr2202.html#abs-2202-08485
Tong Zhao 0003
Gang Liu 0025
Stephan Günnemann
Meng Jiang 0001
Graph Data Augmentation for Graph Machine Learning: A Survey.
2022
abs/2202.08871
CoRR
https://arxiv.org/abs/2202.08871
db/journals/corr/corr2202.html#abs-2202-08871
Armin Moin
Ukrit Wattanavaekin
Alexandra Lungu
Moharram Challenger
Atta Badii
Stephan Günnemann
Enabling Automated Machine Learning for Model-Driven AI Engineering.
2022
abs/2203.02927
CoRR
https://doi.org/10.48550/arXiv.2203.02927
db/journals/corr/corr2203.html#abs-2203-02927
Bertrand Charpentier
Simon Kibler
Stephan Günnemann
Differentiable DAG Sampling.
2022
abs/2203.08509
CoRR
https://doi.org/10.48550/arXiv.2203.08509
db/journals/corr/corr2203.html#abs-2203-08509
Poulami Sinhamahapatra
Rajat Koner
Karsten Roscher
Stephan Günnemann
Is it all a cluster game? - Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space.
2022
abs/2203.08549
CoRR
https://doi.org/10.48550/arXiv.2203.08549
db/journals/corr/corr2203.html#abs-2203-08549
Marten Lienen
Stephan Günnemann
Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks.
2022
abs/2203.08852
CoRR
https://doi.org/10.48550/arXiv.2203.08852
db/journals/corr/corr2203.html#abs-2203-08852
Johannes Gasteiger
Muhammed Shuaibi
Anuroop Sriram
Stephan Günnemann
Zachary W. Ulissi
C. Lawrence Zitnick
Abhishek Das
How Do Graph Networks Generalize to Large and Diverse Molecular Systems?
2022
abs/2204.02782
CoRR
https://doi.org/10.48550/arXiv.2204.02782
db/journals/corr/corr2204.html#abs-2204-02782
Leon Hetzel
Simon Böhm
Niki Kilbertus
Stephan Günnemann
Mohammad Lotfollahi
Fabian J. Theis
Predicting single-cell perturbation responses for unseen drugs.
2022
abs/2204.13545
CoRR
https://doi.org/10.48550/arXiv.2204.13545
db/journals/corr/corr2204.html#abs-2204-13545
Nicholas Gao
Stephan Günnemann
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks.
2022
abs/2205.14962
CoRR
https://doi.org/10.48550/arXiv.2205.14962
db/journals/corr/corr2205.html#abs-2205-14962
Bertrand Charpentier
Ransalu Senanayake
Mykel J. Kochenderfer
Stephan Günnemann
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning.
2022
abs/2206.01558
CoRR
https://doi.org/10.48550/arXiv.2206.01558
db/journals/corr/corr2206.html#abs-2206-01558
John Rachwan
Daniel Zügner
Bertrand Charpentier
Simon Geisler
Morgane Ayle
Stephan Günnemann
Winning the Lottery Ahead of Time: Efficient Early Network Pruning.
2022
abs/2206.10451
CoRR
https://doi.org/10.48550/arXiv.2206.10451
db/journals/corr/corr2206.html#abs-2206-10451
Morgane Ayle
Bertrand Charpentier
John Rachwan
Daniel Zügner
Simon Geisler
Stephan Günnemann
On the Robustness and Anomaly Detection of Sparse Neural Networks.
2022
abs/2207.04227
CoRR
https://doi.org/10.48550/arXiv.2207.04227
db/journals/corr/corr2207.html#abs-2207-04227
Jonathan Külz
Andreas Spitz
Ahmad Abu-Akel
Stephan Günnemann
Robert West 0001
United States Politicians' Tone Became More Negative with 2016 Primary Campaigns.
2022
abs/2207.08112
CoRR
https://doi.org/10.48550/arXiv.2207.08112
db/journals/corr/corr2207.html#abs-2207-08112
Jörg Christian Kirchhof
Evgeny Kusmenko
Jonas Ritz
Bernhard Rumpe
Armin Moin
Atta Badii
Stephan Günnemann
Moharram Challenger
MDE for Machine Learning-Enabled Software Systems: A Case Study and Comparison of MontiAnna & ML-Quadrat.
2022
abs/2209.07282
CoRR
https://doi.org/10.48550/arXiv.2209.07282
db/journals/corr/corr2209.html#abs-2209-07282
Alexandru Mara
Jefrey Lijffijt
Stephan Günnemann
Tijl De Bie
A Systematic Evaluation of Node Embedding Robustness.
2022
abs/2209.08064
CoRR
https://doi.org/10.48550/arXiv.2209.08064
db/journals/corr/corr2209.html#abs-2209-08064
Raffaele Paolino
Aleksandar Bojchevski
Stephan Günnemann
Gitta Kutyniok
Ron Levie
Unveiling the Sampling Density in Non-Uniform Geometric Graphs.
2022
abs/2210.08219
CoRR
https://doi.org/10.48550/arXiv.2210.08219
db/journals/corr/corr2210.html#abs-2210-08219
Marin Bilos
Emanuel Ramneantu
Stephan Günnemann
Irregularly-Sampled Time Series Modeling with Spline Networks.
2022
abs/2210.10630
CoRR
https://doi.org/10.48550/arXiv.2210.10630
db/journals/corr/corr2210.html#abs-2210-10630
Marten Lienen
Stephan Günnemann
torchode: A Parallel ODE Solver for PyTorch.
2022
abs/2210.12375
CoRR
https://doi.org/10.48550/arXiv.2210.12375
db/journals/corr/corr2210.html#abs-2210-12375
Jan Schuchardt
Tom Wollschläger
Aleksandar Bojchevski
Stephan Günnemann
Localized Randomized Smoothing for Collective Robustness Certification.
2022
abs/2210.16140
CoRR
https://doi.org/10.48550/arXiv.2210.16140
db/journals/corr/corr2210.html#abs-2210-16140
Marin Bilos
Kashif Rasul
Anderson Schneider
Yuriy Nevmyvaka
Stephan Günnemann
Modeling Temporal Data as Continuous Functions with Process Diffusion.
2022
abs/2211.02590
CoRR
https://doi.org/10.48550/arXiv.2211.02590
db/journals/corr/corr2211.html#abs-2211-02590
Jan Schuchardt
Stephan Günnemann
Invariance-Aware Randomized Smoothing Certificates.
2022
abs/2211.14207
CoRR
https://doi.org/10.48550/arXiv.2211.14207
db/journals/corr/corr2211.html#abs-2211-14207
Johannes Gasteiger
Chendi Qian
Stephan Günnemann
Influence-Based Mini-Batching for Graph Neural Networks.
2022
abs/2212.09083
CoRR
https://doi.org/10.48550/arXiv.2212.09083
db/journals/corr/corr2212.html#abs-2212-09083
Martin Grohe
Stephan Günnemann
Stefanie Jegelka
Christopher Morris 0001
Graph Embeddings: Theory meets Practice (Dagstuhl Seminar 22132).
141-155
2022
12
Dagstuhl Reports
3
https://doi.org/10.4230/DagRep.12.3.141
db/journals/dagstuhl-reports/dagstuhl-reports12.html#GroheGJ022
Martin Atzmueller
Stephan Günnemann
Albrecht Zimmermann
Mining communities and their descriptions on attributed graphs: a survey.
661-687
2021
35
Data Min. Knowl. Discov.
3
https://doi.org/10.1007/s10618-021-00741-z
https://www.wikidata.org/entity/Q113302589
db/journals/datamine/datamine35.html#AtzmuellerGZ21
Anna-Kathrin Kopetzki
Stephan Günnemann
Reachable sets of classifiers and regression models: (non-)robustness analysis and robust training.
1175-1197
2021
110
Mach. Learn.
6
https://doi.org/10.1007/s10994-021-05973-0
db/journals/ml/ml110.html#KopetzkiG21
Yihan Wu
Aleksandar Bojchevski
Aleksei Kuvshinov
Stephan Günnemann
Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions.
3763-3771
2021
AISTATS
http://proceedings.mlr.press/v130/wu21d.html
conf/aistats/2021
db/conf/aistats/aistats2021.html#WuBKG21
Rajat Koner
Poulami Sinhamahapatra
Karsten Roscher
Stephan Günnemann
Volker Tresp
OODformer: Out-Of-Distribution Detection Transformer.
209
2021
BMVC
https://www.bmvc2021-virtualconference.com/assets/papers/1391.pdf
conf/bmvc/2021
db/conf/bmvc/bmvc2021.html#KonerSRGT21
Jan Schuchardt
Aleksandar Bojchevski
Johannes Klicpera
Stephan Günnemann
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks.
2021
ICLR
https://openreview.net/forum?id=ULQdiUTHe3y
conf/iclr/2021
db/conf/iclr/iclr2021.html#SchuchardtBKG21
Daniel Zügner
Tobias Kirschstein
Michele Catasta
Jure Leskovec
Stephan Günnemann
Language-Agnostic Representation Learning of Source Code from Structure and Context.
2021
ICLR
https://openreview.net/forum?id=Xh5eMZVONGF
conf/iclr/2021
db/conf/iclr/iclr2021.html#ZugnerKCLG21
Marin Bilos
Stephan Günnemann
Scalable Normalizing Flows for Permutation Invariant Densities.
957-967
2021
ICML
http://proceedings.mlr.press/v139/bilos21a.html
conf/icml/2021
db/conf/icml/icml2021.html#BilosG21
Johannes Klicpera
Marten Lienen
Stephan Günnemann
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More.
5616-5627
2021
ICML
http://proceedings.mlr.press/v139/klicpera21a.html
conf/icml/2021
db/conf/icml/icml2021.html#KlicperaLG21
Anna-Kathrin Kopetzki
Bertrand Charpentier
Daniel Zügner
Sandhya Giri
Stephan Günnemann
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
5707-5718
2021
ICML
http://proceedings.mlr.press/v139/kopetzki21a.html
conf/icml/2021
db/conf/icml/icml2021.html#KopetzkiCZGG21
Tom Haider
Felippe Schmoeller Roza
Dirk Eilers
Karsten Roscher
Stephan Günnemann
Domain Shifts in Reinforcement Learning: Identifying Disturbances in Environments.
2021
AISafety@IJCAI
https://ceur-ws.org/Vol-2916/paper_11.pdf
conf/ijcai/2021aisafety
db/conf/ijcai/aisafety2021.html#HaiderRERG21
Oleksandr Shchur
Ali Caner Türkmen
Tim Januschowski
Stephan Günnemann
Neural Temporal Point Processes: A Review.
4585-4593
2021
IJCAI
https://doi.org/10.24963/ijcai.2021/623
conf/ijcai/2021
db/conf/ijcai/ijcai2021.html#ShchurTJG21
Johannes Gasteiger
Florian Becker
Stephan Günnemann
GemNet: Universal Directional Graph Neural Networks for Molecules.
6790-6802
2021
NeurIPS
https://proceedings.neurips.cc/paper/2021/hash/35cf8659cfcb13224cbd47863a34fc58-Abstract.html
conf/nips/2021
db/conf/nips/neurips2021.html#GasteigerBG21
Simon Geisler
Tobias Schmidt
Hakan Sirin
Daniel Zügner
Aleksandar Bojchevski
Stephan Günnemann
Robustness of Graph Neural Networks at Scale.
7637-7649
2021
NeurIPS
https://proceedings.neurips.cc/paper/2021/hash/3ea2db50e62ceefceaf70a9d9a56a6f4-Abstract.html
conf/nips/2021
db/conf/nips/neurips2021.html#GeislerSSZBG21
Johannes Gasteiger
Chandan Yeshwanth
Stephan Günnemann
Directional Message Passing on Molecular Graphs via Synthetic Coordinates.
15421-15433
2021
NeurIPS
https://proceedings.neurips.cc/paper/2021/hash/82489c9737cc245530c7a6ebef3753ec-Abstract.html
conf/nips/2021
db/conf/nips/neurips2021.html#GasteigerYG21
Marin Bilos
Johanna Sommer
Syama Sundar Rangapuram
Tim Januschowski
Stephan Günnemann
Neural Flows: Efficient Alternative to Neural ODEs.
21325-21337
2021
NeurIPS
https://proceedings.neurips.cc/paper/2021/hash/b21f9f98829dea9a48fd8aaddc1f159d-Abstract.html
conf/nips/2021
db/conf/nips/neurips2021.html#BilosSRJG21
Johannes C. Paetzold
Julian McGinnis
Suprosanna Shit
Ivan Ezhov
Paul Büschl
Chinmay Prabhakar
Anjany Sekuboyina
Mihail I. Todorov
Georgios Kaissis
Ali Ertürk
Stephan Günnemann
Bjoern H. Menze
Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience.
2021
NeurIPS Datasets and Benchmarks
https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/c9f0f895fb98ab9159f51fd0297e236d-Abstract-round2.html
conf/nips/2021db
db/conf/nips/neurips2021db.html#PaetzoldMSEBPST21
Oleksandr Shchur
Ali Caner Türkmen
Tim Januschowski
Jan Gasthaus
Stephan Günnemann
Detecting Anomalous Event Sequences with Temporal Point Processes.
13419-13431
2021
NeurIPS
https://proceedings.neurips.cc/paper/2021/hash/6faa8040da20ef399b63a72d0e4ab575-Abstract.html
conf/nips/2021
db/conf/nips/neurips2021.html#ShchurTJGG21
Maximilian Stadler
Bertrand Charpentier
Simon Geisler
Daniel Zügner
Stephan Günnemann
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification.
18033-18048
2021
NeurIPS
https://proceedings.neurips.cc/paper/2021/hash/95b431e51fc53692913da5263c214162-Abstract.html
conf/nips/2021
db/conf/nips/neurips2021.html#StadlerCGZG21
Rajat Koner
Hang Li 0010
Marcel Hildebrandt
Deepan Das
Volker Tresp
Stephan Günnemann
Graphhopper: Multi-hop Scene Graph Reasoning for Visual Question Answering.
111-127
2021
ISWC
https://doi.org/10.1007/978-3-030-88361-4_7
conf/semweb/2021
db/conf/semweb/iswc2021.html#KonerLHDTG21
Maximilian E. Schüle
Harald Lang
Maximilian Springer
Alfons Kemper
Thomas Neumann 0001
Stephan Günnemann
In-Database Machine Learning with SQL on GPUs.
25-36
2021
SSDBM
https://doi.org/10.1145/3468791.3468840
conf/ssdbm/2021
db/conf/ssdbm/ssdbm2021.html#SchuleLSK0G21
Daniel Zügner
Tobias Kirschstein
Michele Catasta
Jure Leskovec
Stephan Günnemann
Language-Agnostic Representation Learning of Source Code from Structure and Context.
2021
abs/2103.11318
CoRR
https://arxiv.org/abs/2103.11318
db/journals/corr/corr2103.html#abs-2103-11318
Oleksandr Shchur
Ali Caner Türkmen
Tim Januschowski
Stephan Günnemann
Neural Temporal Point Processes: A Review.
2021
abs/2104.03528
CoRR
https://arxiv.org/abs/2104.03528
db/journals/corr/corr2104.html#abs-2104-03528
Bertrand Charpentier
Oliver Borchert
Daniel Zügner
Simon Geisler
Stephan Günnemann
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions.
2021
abs/2105.04471
CoRR
https://arxiv.org/abs/2105.04471
db/journals/corr/corr2105.html#abs-2105-04471
Oleksandr Shchur
Ali Caner Türkmen
Tim Januschowski
Jan Gasthaus
Stephan Günnemann
Detecting Anomalous Event Sequences with Temporal Point Processes.
2021
abs/2106.04465
CoRR
https://arxiv.org/abs/2106.04465
db/journals/corr/corr2106.html#abs-2106-04465
Johannes Gasteiger
Florian Becker
Stephan Günnemann
GemNet: Universal Directional Graph Neural Networks for Molecules.
2021
abs/2106.08903
CoRR
https://arxiv.org/abs/2106.08903
db/journals/corr/corr2106.html#abs-2106-08903
Armin Moin
Atta Badii
Stephan Günnemann
A Model-Driven Engineering Approach to Machine Learning and Software Modeling.
2021
abs/2107.02689
CoRR
https://arxiv.org/abs/2107.02689
db/journals/corr/corr2107.html#abs-2107-02689
Armin Moin
Atta Badii
Stephan Günnemann
Enabling Un-/Semi-Supervised Machine Learning for MDSE of the Real-World CPS/IoT Applications.
2021
abs/2107.02690
CoRR
https://arxiv.org/abs/2107.02690
db/journals/corr/corr2107.html#abs-2107-02690
Armin Moin
Andrei Mituca
Atta Badii
Stephan Günnemann
ML-Quadrat & DriotData: A Model-Driven Engineering Tool and a Low-Code Platform for Smart IoT Services.
2021
abs/2107.02692
CoRR
https://arxiv.org/abs/2107.02692
db/journals/corr/corr2107.html#abs-2107-02692
Rajat Koner
Hang Li 0010
Marcel Hildebrandt
Deepan Das
Volker Tresp
Stephan Günnemann
Graphhopper: Multi-Hop Scene Graph Reasoning for Visual Question Answering.
2021
abs/2107.06325
CoRR
https://arxiv.org/abs/2107.06325
db/journals/corr/corr2107.html#abs-2107-06325
Armin Moin
Moharram Challenger
Atta Badii
Stephan Günnemann
MDE4QAI: Towards Model-Driven Engineering for Quantum Artificial Intelligence.
2021
abs/2107.06708
CoRR
https://arxiv.org/abs/2107.06708
db/journals/corr/corr2107.html#abs-2107-06708
Johannes Klicpera
Marten Lienen
Stephan Günnemann
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More.
2021
abs/2107.06876
CoRR
https://arxiv.org/abs/2107.06876
db/journals/corr/corr2107.html#abs-2107-06876
Sven Elflein
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
On Out-of-distribution Detection with Energy-based Models.
2021
abs/2107.08785
CoRR
https://arxiv.org/abs/2107.08785
db/journals/corr/corr2107.html#abs-2107-08785
Rajat Koner
Poulami Sinhamahapatra
Karsten Roscher
Stephan Günnemann
Volker Tresp
OODformer: Out-Of-Distribution Detection Transformer.
2021
abs/2107.08976
CoRR
https://arxiv.org/abs/2107.08976
db/journals/corr/corr2107.html#abs-2107-08976
Johannes C. Paetzold
Julian McGinnis
Suprosanna Shit
Ivan Ezhov
Paul Büschl
Chinmay Prabhakar
Mihail I. Todorov
Anjany Sekuboyina
Georgios Kaissis
Ali Ertürk
Stephan Günnemann
Bjoern H. Menze
Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience (VesselGraph).
2021
abs/2108.13233
CoRR
https://arxiv.org/abs/2108.13233
db/journals/corr/corr2108.html#abs-2108-13233
Sebastian Bischoff 0001
Stephan Günnemann
Martin Jaggi
Sebastian U. Stich
On Second-order Optimization Methods for Federated Learning.
2021
abs/2109.02388
CoRR
https://arxiv.org/abs/2109.02388
db/journals/corr/corr2109.html#abs-2109-02388
Daniel Zügner
François-Xavier Aubet
Victor Garcia Satorras
Tim Januschowski
Stephan Günnemann
Jan Gasthaus
A Study of Joint Graph Inference and Forecasting.
2021
abs/2109.04979
CoRR
https://arxiv.org/abs/2109.04979
db/journals/corr/corr2109.html#abs-2109-04979
Hannes Stärk
Dominique Beaini
Gabriele Corso
Prudencio Tossou
Christian Dallago
Stephan Günnemann
Pietro Liò
3D Infomax improves GNNs for Molecular Property Prediction.
2021
abs/2110.04126
CoRR
https://arxiv.org/abs/2110.04126
db/journals/corr/corr2110.html#abs-2110-04126
Nicholas Gao
Stephan Günnemann
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions.
2021
abs/2110.05064
CoRR
https://arxiv.org/abs/2110.05064
db/journals/corr/corr2110.html#abs-2110-05064
Peter Súkeník
Aleksei Kuvshinov
Stephan Günnemann
Intriguing Properties of Input-dependent Randomized Smoothing.
2021
abs/2110.05365
CoRR
https://arxiv.org/abs/2110.05365
db/journals/corr/corr2110.html#abs-2110-05365
Simon Geisler
Johanna Sommer
Jan Schuchardt
Aleksandar Bojchevski
Stephan Günnemann
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness.
2021
abs/2110.10942
CoRR
https://arxiv.org/abs/2110.10942
db/journals/corr/corr2110.html#abs-2110-10942
Marin Bilos
Johanna Sommer
Syama Sundar Rangapuram
Tim Januschowski
Stephan Günnemann
Neural Flows: Efficient Alternative to Neural ODEs.
2021
abs/2110.13040
CoRR
https://arxiv.org/abs/2110.13040
db/journals/corr/corr2110.html#abs-2110-13040
Maximilian Stadler
Bertrand Charpentier
Simon Geisler
Daniel Zügner
Stephan Günnemann
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification.
2021
abs/2110.14012
CoRR
https://arxiv.org/abs/2110.14012
db/journals/corr/corr2110.html#abs-2110-14012
Simon Geisler
Tobias Schmidt
Hakan Sirin
Daniel Zügner
Aleksandar Bojchevski
Stephan Günnemann
Robustness of Graph Neural Networks at Scale.
2021
abs/2110.14038
CoRR
https://arxiv.org/abs/2110.14038
db/journals/corr/corr2110.html#abs-2110-14038
Johannes Klicpera
Chandan Yeshwanth
Stephan Günnemann
Directional Message Passing on Molecular Graphs via Synthetic Coordinates.
2021
abs/2111.04718
CoRR
https://arxiv.org/abs/2111.04718
db/journals/corr/corr2111.html#abs-2111-04718
Daniel Zügner
Oliver Borchert
Amir Akbarnejad
Stephan Günnemann
Adversarial Attacks on Graph Neural Networks: Perturbations and their Patterns.
57:1-57:31
2020
14
ACM Trans. Knowl. Discov. Data
5
https://doi.org/10.1145/3394520
https://www.wikidata.org/entity/Q114822532
db/journals/tkdd/tkdd14.html#ZugnerBAG20
Zhen Han
Yunpu Ma
Yuyi Wang 0001
Stephan Günnemann
Volker Tresp
Graph Hawkes Neural Network for Forecasting on Temporal Knowledge Graphs.
2020
AKBC
https://doi.org/10.24432/C50018
conf/akbc/2020
db/conf/akbc/akbc2020.html#HanM0GT20
Eugenio Angriman
Alexander van der Grinten
Aleksandar Bojchevski
Daniel Zügner
Stephan Günnemann
Henning Meyerhenke
Group Centrality Maximization for Large-scale Graphs.
56-69
2020
ALENEX
https://doi.org/10.1137/1.9781611976007.5
conf/alenex/2020
db/conf/alenex/alenex2020.html#AngrimanGBZGM20
Felippe Schmoeller Roza
Maximilian Henne
Karsten Roscher
Stephan Günnemann
Assessing Box Merging Strategies and Uncertainty Estimation Methods in Multimodel Object Detection.
3-10
2020
ECCV Workshops (6)
https://doi.org/10.1007/978-3-030-65414-6_1
conf/eccv/2020-w6
db/conf/eccv/eccv2020-w6.html#RozaHRG20
Johannes Klicpera
Janek Groß
Stephan Günnemann
Directional Message Passing for Molecular Graphs.
2020
ICLR
https://openreview.net/forum?id=B1eWbxStPH
conf/iclr/2020
db/conf/iclr/iclr2020.html#KlicperaGG20
Richard Kurle
Botond Cseke
Alexej Klushyn
Patrick van der Smagt
Stephan Günnemann
Continual Learning with Bayesian Neural Networks for Non-Stationary Data.
2020
ICLR
https://openreview.net/forum?id=SJlsFpVtDB
conf/iclr/2020
db/conf/iclr/iclr2020.html#KurleCKSG20
Oleksandr Shchur
Marin Bilos
Stephan Günnemann
Intensity-Free Learning of Temporal Point Processes.
2020
ICLR
https://openreview.net/forum?id=HygOjhEYDH
conf/iclr/2020
db/conf/iclr/iclr2020.html#ShchurBG20
Aleksandar Bojchevski
Johannes Klicpera
Stephan Günnemann
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More.
1003-1013
2020
ICML
http://proceedings.mlr.press/v119/bojchevski20a.html
conf/icml/2020
db/conf/icml/icml2020.html#BojchevskiKG20
Daniel Zügner
Stephan Günnemann
Certifiable Robustness of Graph Convolutional Networks under Structure Perturbations.
1656-1665
2020
KDD
https://doi.org/10.1145/3394486.3403217
conf/kdd/2020
db/conf/kdd/kdd2020.html#ZugnerG20
Aleksandar Bojchevski
Johannes Klicpera
Bryan Perozzi
Amol Kapoor
Martin Blais
Benedek Rózemberczki
Michal Lukasik
Stephan Günnemann
Scaling Graph Neural Networks with Approximate PageRank.
2464-2473
2020
KDD
https://doi.org/10.1145/3394486.3403296
conf/kdd/2020
db/conf/kdd/kdd2020.html#BojchevskiKPKBR20
Armin Moin
Stephan Rössler
Marouane Sayih
Stephan Günnemann
From things' modeling language (ThingML) to things' machine learning (ThingML2).
19:1-19:2
2020
MoDELS (Companion)
https://doi.org/10.1145/3417990.3420057
conf/models/2020c
db/conf/models/models2020c.html#MoinRSG20
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts.
2020
NeurIPS
https://proceedings.neurips.cc/paper/2020/hash/0eac690d7059a8de4b48e90f14510391-Abstract.html
conf/nips/2020
db/conf/nips/neurips2020.html#CharpentierZG20
Simon Geisler
Daniel Zügner
Stephan Günnemann
Reliable Graph Neural Networks via Robust Aggregation.
2020
NeurIPS
https://proceedings.neurips.cc/paper/2020/hash/99e314b1b43706773153e7ef375fc68c-Abstract.html
conf/nips/2020
db/conf/nips/neurips2020.html#GeislerZG20
Richard Kurle
Syama Sundar Rangapuram
Emmanuel de Bézenac
Stephan Günnemann
Jan Gasthaus
Deep Rao-Blackwellised Particle Filters for Time Series Forecasting.
2020
NeurIPS
https://proceedings.neurips.cc/paper/2020/hash/afb0b97df87090596ae7c503f60bb23f-Abstract.html
conf/nips/2020
db/conf/nips/neurips2020.html#KurleRBGG20
Oleksandr Shchur
Nicholas Gao
Marin Bilos
Stephan Günnemann
Fast and Flexible Temporal Point Processes with Triangular Maps.
2020
NeurIPS
https://proceedings.neurips.cc/paper/2020/hash/00ac8ed3b4327bdd4ebbebcb2ba10a00-Abstract.html
conf/nips/2020
db/conf/nips/neurips2020.html#ShchurGBG20
Richard Leibrandt
Stephan Günnemann
Gauss Shift: Density Attractor Clustering Faster Than Mean Shift.
125-142
2020
ECML/PKDD (1)
https://doi.org/10.1007/978-3-030-67658-2_8
conf/pkdd/2020-1
db/conf/pkdd/pkdd2020-1.html#LeibrandtG20
Johannes Klicpera
Janek Groß
Stephan Günnemann
Directional Message Passing for Molecular Graphs.
2020
abs/2003.03123
CoRR
https://arxiv.org/abs/2003.03123
db/journals/corr/corr2003.html#abs-2003-03123
Zhen Han
Yuyi Wang 0001
Yunpu Ma
Stephan Günnemann
Volker Tresp
Graph Hawkes Network for Reasoning on Temporal Knowledge Graphs.
2020
abs/2003.13432
CoRR
https://arxiv.org/abs/2003.13432
db/journals/corr/corr2003.html#abs-2003-13432
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts.
2020
abs/2006.09239
CoRR
https://arxiv.org/abs/2006.09239
db/journals/corr/corr2006.html#abs-2006-09239
Oleksandr Shchur
Nicholas Gao
Marin Bilos
Stephan Günnemann
Fast and Flexible Temporal Point Processes with Triangular Maps.
2020
abs/2006.12631
CoRR
https://arxiv.org/abs/2006.12631
db/journals/corr/corr2006.html#abs-2006-12631
Marcel Hildebrandt
Hang Li 0010
Rajat Koner
Volker Tresp
Stephan Günnemann
Scene Graph Reasoning for Visual Question Answering.
2020
abs/2007.01072
CoRR
https://arxiv.org/abs/2007.01072
db/journals/corr/corr2007.html#abs-2007-01072
Aleksandar Bojchevski
Johannes Klicpera
Bryan Perozzi
Amol Kapoor
Martin Blais
Benedek Rózemberczki
Michal Lukasik
Stephan Günnemann
Scaling Graph Neural Networks with Approximate PageRank.
2020
abs/2007.01570
CoRR
https://arxiv.org/abs/2007.01570
db/journals/corr/corr2007.html#abs-2007-01570
Nick Harmening
Marin Bilos
Stephan Günnemann
Deep Representation Learning and Clustering of Traffic Scenarios.
2020
abs/2007.07740
CoRR
https://arxiv.org/abs/2007.07740
db/journals/corr/corr2007.html#abs-2007-07740
Anna-Kathrin Kopetzki
Stephan Günnemann
Reachable Sets of Classifiers & Regression Models: (Non-)Robustness Analysis and Robust Training.
2020
abs/2007.14120
CoRR
https://arxiv.org/abs/2007.14120
db/journals/corr/corr2007.html#abs-2007-14120
Aleksandar Bojchevski
Johannes Klicpera
Stephan Günnemann
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More.
2020
abs/2008.12952
CoRR
https://arxiv.org/abs/2008.12952
db/journals/corr/corr2008.html#abs-2008-12952
Armin Moin
Stephan Rössler
Marouane Sayih
Stephan Günnemann
From Things' Modeling Language (ThingML) to Things' Machine Learning (ThingML2).
2020
abs/2009.10632
CoRR
https://arxiv.org/abs/2009.10632
db/journals/corr/corr2009.html#abs-2009-10632
Armin Moin
Stephan Rössler
Stephan Günnemann
ThingML+ Augmenting Model-Driven Software Engineering for the Internet of Things with Machine Learning.
2020
abs/2009.10633
CoRR
https://arxiv.org/abs/2009.10633
db/journals/corr/corr2009.html#abs-2009-10633
Marin Bilos
Stephan Günnemann
Equivariant Normalizing Flows for Point Processes and Sets.
2020
abs/2010.03242
CoRR
https://arxiv.org/abs/2010.03242
db/journals/corr/corr2010.html#abs-2010-03242
Anna-Kathrin Kopetzki
Bertrand Charpentier
Daniel Zügner
Sandhya Giri
Stephan Günnemann
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
2020
abs/2010.14986
CoRR
https://arxiv.org/abs/2010.14986
db/journals/corr/corr2010.html#abs-2010-14986
Simon Geisler
Daniel Zügner
Stephan Günnemann
Reliable Graph Neural Networks via Robust Aggregation.
2020
abs/2010.15651
CoRR
https://arxiv.org/abs/2010.15651
db/journals/corr/corr2010.html#abs-2010-15651
Johannes Klicpera
Shankari Giri
Johannes T. Margraf
Stephan Günnemann
Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules.
2020
abs/2011.14115
CoRR
https://arxiv.org/abs/2011.14115
db/journals/corr/corr2011.html#abs-2011-14115
Saskia Metzler
Stephan Günnemann
Pauli Miettinen
Stability and dynamics of communities on online question-answer sites.
50-58
2019
58
Soc. Networks
https://doi.org/10.1016/j.socnet.2018.12.004
db/journals/socnet/socnet58.html#MetzlerGM19
Richard Kurle
Stephan Günnemann
Patrick van der Smagt
Multi-Source Neural Variational Inference.
4114-4121
2019
AAAI
https://doi.org/10.1609/aaai.v33i01.33014114
conf/aaai/2019
db/conf/aaai/aaai2019.html#KurleGS19
Maximilian E. Schüle
Frédéric Simonis
Thomas Heyenbrock
Alfons Kemper
Stephan Günnemann
Thomas Neumann 0001
In-Database Machine Learning: Gradient Descent and Tensor Algebra for Main Memory Database Systems.
247-266
2019
BTW
https://doi.org/10.18420/btw2019-16
conf/btw/2019
db/conf/btw/btw2019.html#SchuleSHKG019
Artur Mrowca
Martin Nocker
Sebastian Steinhorst
Stephan Günnemann
Learning Temporal Specifications from Imperfect Traces Using Bayesian Inference.
96
2019
DAC
https://doi.org/10.1145/3316781.3317847
https://ieeexplore.ieee.org/document/8807059
conf/dac/2019
db/conf/dac/dac2019.html#MrowcaNSG19
Maximilian E. Schüle
Dimitri Vorona
Linnea Passing
Harald Lang
Alfons Kemper
Stephan Günnemann
Thomas Neumann 0001
The Power of SQL Lambda Functions.
534-537
2019
EDBT
https://doi.org/10.5441/002/edbt.2019.49
conf/edbt/2019
db/conf/edbt/edbt2019.html#SchuleVPLKG019
Maximilian E. Schüle
Matthias Bungeroth
Dimitri Vorona
Alfons Kemper
Stephan Günnemann
Thomas Neumann 0001
ML2SQL - Compiling a Declarative Machine Learning Language to SQL and Python.
562-565
2019
EDBT
https://doi.org/10.5441/002/edbt.2019.56
conf/edbt/2019
db/conf/edbt/edbt2019.html#SchuleBVKG019
Daniel Zügner
Amir Akbarnejad
Stephan Günnemann
Adversarial Attacks on Graph Neural Networks.
251-252
2019
GI-Jahrestagung
https://doi.org/10.18420/inf2019_29
conf/gi/2019
db/conf/gi/gi2019.html#ZugnerAG19
Johannes Klicpera
Aleksandar Bojchevski
Stephan Günnemann
Predict then Propagate: Graph Neural Networks meet Personalized PageRank.
2019
ICLR (Poster)
https://openreview.net/forum?id=H1gL-2A9Ym
conf/iclr/2019
db/conf/iclr/iclr2019.html#KlicperaBG19
Daniel Zügner
Stephan Günnemann
Adversarial Attacks on Graph Neural Networks via Meta Learning.
2019
ICLR (Poster)
https://openreview.net/forum?id=Bylnx209YX
conf/iclr/2019
db/conf/iclr/iclr2019.html#ZugnerG19
Aleksandar Bojchevski
Stephan Günnemann
Adversarial Attacks on Node Embeddings via Graph Poisoning.
695-704
2019
ICML
http://proceedings.mlr.press/v97/bojchevski19a.html
conf/icml/2019
db/conf/icml/icml2019.html#BojchevskiG19
Daniel Zügner
Amir Akbarnejad
Stephan Günnemann
Adversarial Attacks on Neural Networks for Graph Data.
2019
IJCAI
https://doi.org/10.24963/ijcai.2019/872
conf/ijcai/2019
db/conf/ijcai/ijcai2019.html#ZugnerAG19
6246-6250
Daniel Zügner
Stephan Günnemann
Certifiable Robustness and Robust Training for Graph Convolutional Networks.
246-256
2019
KDD
https://doi.org/10.1145/3292500.3330905
conf/kdd/2019
db/conf/kdd/kdd2019.html#ZugnerG19
Stephan Rabanser
Stephan Günnemann
Zachary C. Lipton
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift.
1394-1406
2019
NeurIPS
https://proceedings.neurips.cc/paper/2019/hash/846c260d715e5b854ffad5f70a516c88-Abstract.html
http://papers.nips.cc/paper/8420-failing-loudly-an-empirical-study-of-methods-for-detecting-dataset-shift
conf/nips/2019
db/conf/nips/nips2019.html#RabanserGL19
Aleksandar Bojchevski
Stephan Günnemann
Certifiable Robustness to Graph Perturbations.
8317-8328
2019
NeurIPS
https://proceedings.neurips.cc/paper/2019/hash/e2f374c3418c50bc30d67d5f7454a5b4-Abstract.html
http://papers.nips.cc/paper/9041-certifiable-robustness-to-graph-perturbations
conf/nips/2019
db/conf/nips/nips2019.html#BojchevskiG19
Bertrand Charpentier
Marin Bilos
Stephan Günnemann
Uncertainty on Asynchronous Time Event Prediction.
12831-12840
2019
NeurIPS
https://proceedings.neurips.cc/paper/2019/hash/78efce208a5242729d222e7e6e3e565e-Abstract.html
http://papers.nips.cc/paper/9445-uncertainty-on-asynchronous-time-event-prediction
conf/nips/2019
db/conf/nips/nips2019.html#CharpentierBG19
Johannes Klicpera
Stefan Weißenberger
Stephan Günnemann
Diffusion Improves Graph Learning.
13333-13345
2019
NeurIPS
https://proceedings.neurips.cc/paper/2019/hash/23c894276a2c5a16470e6a31f4618d73-Abstract.html
http://papers.nips.cc/paper/9490-diffusion-improves-graph-learning
conf/nips/2019
db/conf/nips/nips2019.html#KlicperaWG19
Maximilian E. Schüle
Matthias Bungeroth
Alfons Kemper
Stephan Günnemann
Thomas Neumann 0001
MLearn: A Declarative Machine Learning Language for Database Systems.
7:1-7:4
2019
DEEM@SIGMOD
https://doi.org/10.1145/3329486.3329494
conf/sigmod/2019deem
db/conf/sigmod/deem2019.html#SchuleBKG019
Subhabrata Mukherjee
Stephan Günnemann
GhostLink: Latent Network Inference for Influence-aware Recommendation.
1310-1320
2019
WWW
https://doi.org/10.1145/3308558.3313449
conf/www/2019
db/conf/www/www2019.html#MukherjeeG19
Daniel Zügner
Stephan Günnemann
Adversarial Attacks on Graph Neural Networks via Meta Learning.
2019
abs/1902.08412
CoRR
http://arxiv.org/abs/1902.08412
db/journals/corr/corr1902.html#abs-1902-08412
Subhabrata Mukherjee
Stephan Günnemann
GhostLink: Latent Network Inference for Influence-aware Recommendation.
2019
abs/1905.05955
CoRR
http://arxiv.org/abs/1905.05955
db/journals/corr/corr1905.html#abs-1905-05955
Daniel Zügner
Stephan Günnemann
Certifiable Robustness and Robust Training for Graph Convolutional Networks.
2019
abs/1906.12269
CoRR
http://arxiv.org/abs/1906.12269
db/journals/corr/corr1906.html#abs-1906-12269
Oleksandr Shchur
Marin Bilos
Stephan Günnemann
Intensity-Free Learning of Temporal Point Processes.
2019
abs/1909.12127
CoRR
http://arxiv.org/abs/1909.12127
db/journals/corr/corr1909.html#abs-1909-12127
Oleksandr Shchur
Stephan Günnemann
Overlapping Community Detection with Graph Neural Networks.
2019
abs/1909.12201
CoRR
http://arxiv.org/abs/1909.12201
db/journals/corr/corr1909.html#abs-1909-12201
Eugenio Angriman
Alexander van der Grinten
Aleksandar Bojchevski
Daniel Zügner
Stephan Günnemann
Henning Meyerhenke
Group Centrality Maximization for Large-scale Graphs.
2019
abs/1910.13874
CoRR
http://arxiv.org/abs/1910.13874
db/journals/corr/corr1910.html#abs-1910-13874
Aleksandar Bojchevski
Stephan Günnemann
Certifiable Robustness to Graph Perturbations.
2019
abs/1910.14356
CoRR
http://arxiv.org/abs/1910.14356
db/journals/corr/corr1910.html#abs-1910-14356
Johannes Klicpera
Stefan Weißenberger
Stephan Günnemann
Diffusion Improves Graph Learning.
2019
abs/1911.05485
CoRR
http://arxiv.org/abs/1911.05485
db/journals/corr/corr1911.html#abs-1911-05485
Marin Bilos
Bertrand Charpentier
Stephan Günnemann
Uncertainty on Asynchronous Time Event Prediction.
2019
abs/1911.05503
CoRR
http://arxiv.org/abs/1911.05503
db/journals/corr/corr1911.html#abs-1911-05503
Alexander Ziller
Julius Hansjakob
Vitalii Rusinov
Daniel Zügner
Peter Vogel
Stephan Günnemann
Oktoberfest Food Dataset.
2019
abs/1912.05007
CoRR
http://arxiv.org/abs/1912.05007
db/journals/corr/corr1912.html#abs-1912-05007
Aleksandar Bojchevski
Stephan Günnemann
Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure.
2018
AAAI
https://doi.org/10.1609/aaai.v32i1.11642
conf/aaai/2018
db/conf/aaai/aaai2018.html#BojchevskiG18
2738-2745
Oleksandr Shchur
Aleksandar Bojchevski
Mohamed Farghal
Stephan Günnemann
Yusuf Saber
Anomaly Detection in Car-Booking Graphs.
604-607
2018
ICDM Workshops
https://doi.org/10.1109/ICDMW.2018.00093
conf/icdm/2018w
db/conf/icdm/icdm2018w.html#ShchurBFGS18
Aleksandar Bojchevski
Stephan Günnemann
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking.
2018
ICLR (Poster)
https://openreview.net/forum?id=r1ZdKJ-0W
conf/iclr/2018
db/conf/iclr/iclr2018.html#BojchevskiG18
Aleksandar Bojchevski
Oleksandr Shchur
Daniel Zügner
Stephan Günnemann
NetGAN: Generating Graphs via Random Walks.
609-618
2018
ICML
http://proceedings.mlr.press/v80/bojchevski18a.html
conf/icml/2018
db/conf/icml/icml2018.html#BojchevskiSZG18
Peter Wolf
Artur Mrowca
Tam Thanh Nguyen
Bernard Bäker
Stephan Günnemann
Pre-ignition Detection Using Deep Neural Networks: A Step Towards Data-driven Automotive Diagnostics.
176-183
2018
ITSC
https://doi.org/10.1109/ITSC.2018.8569908
conf/itsc/2018
db/conf/itsc/itsc2018.html#WolfMNBG18
Daniel Zügner
Amir Akbarnejad
Stephan Günnemann
Adversarial Attacks on Neural Networks for Graph Data.
2847-2856
2018
KDD
https://doi.org/10.1145/3219819.3220078
conf/kdd/2018
db/conf/kdd/kdd2018.html#ZugnerAG18
Armin Moin
Stephan Rössler
Stephan Günnemann
ThingML+: Augmenting Model-Driven Software Engineering for the Internet of Things with Machine Learning.
521-523
2018
MoDELS (Workshops)
https://ceur-ws.org/Vol-2245/mde4iot_paper_5.pdf
conf/models/2018w
db/conf/models/models2018w.html#RosslerG18
Artur Mrowca
Barbara Moser
Stephan Günnemann
Discovering Groups of Signals in In-Vehicle Network Traces for Redundancy Detection and Functional Grouping.
86-102
2018
ECML/PKDD (3)
https://doi.org/10.1007/978-3-030-10997-4_6
conf/pkdd/2018-3
db/conf/pkdd/pkdd2018-3.html#MrowcaMG18
Marawan Shalaby
Jan Stutzki
Matthias Schubert
Stephan Günnemann
An LSTM Approach to Patent Classification based on Fixed Hierarchy Vectors.
495-503
2018
SDM
https://doi.org/10.1137/1.9781611975321.56
conf/sdm/2018
db/conf/sdm/sdm2018.html#ShalabySSG18
Richard Leibrandt
Stephan Günnemann
Making Kernel Density Estimation Robust towards Missing Values in Highly Incomplete Multivariate Data without Imputation.
747-755
2018
SDM
https://doi.org/10.1137/1.9781611975321.84
conf/sdm/2018
db/conf/sdm/sdm2018.html#LeibrandtG18
Lorenzo von Ritter
Michael E. Houle
Stephan Günnemann
Intrinsic Degree: An Estimator of the Local Growth Rate in Graphs.
195-208
2018
SISAP
https://doi.org/10.1007/978-3-030-02224-2_15
conf/sisap/2018
db/conf/sisap/sisap2018.html#RitterHG18
Aleksandar Bojchevski
Oleksandr Shchur
Daniel Zügner
Stephan Günnemann
NetGAN: Generating Graphs via Random Walks.
2018
abs/1803.00816
CoRR
http://arxiv.org/abs/1803.00816
db/journals/corr/corr1803.html#abs-1803-00816
Daniel Zügner
Amir Akbarnejad
Stephan Günnemann
Adversarial Attacks on Neural Networks for Graph Data.
2018
abs/1805.07984
CoRR
http://arxiv.org/abs/1805.07984
db/journals/corr/corr1805.html#abs-1805-07984
Federico Monti
Oleksandr Shchur
Aleksandar Bojchevski
Or Litany
Stephan Günnemann
Michael M. Bronstein
Dual-Primal Graph Convolutional Networks.
2018
abs/1806.00770
CoRR
http://arxiv.org/abs/1806.00770
db/journals/corr/corr1806.html#abs-1806-00770
Aleksandar Bojchevski
Stephan Günnemann
Adversarial Attacks on Node Embeddings.
2018
abs/1809.01093
CoRR
http://arxiv.org/abs/1809.01093
db/journals/corr/corr1809.html#abs-1809-01093
Roberto Alonso
Stephan Günnemann
Mining Contrasting Quasi-Clique Patterns.
2018
abs/1810.01836
CoRR
http://arxiv.org/abs/1810.01836
db/journals/corr/corr1810.html#abs-1810-01836
Johannes Klicpera
Aleksandar Bojchevski
Stephan Günnemann
Personalized Embedding Propagation: Combining Neural Networks on Graphs with Personalized PageRank.
2018
abs/1810.05997
CoRR
http://arxiv.org/abs/1810.05997
db/journals/corr/corr1810.html#abs-1810-05997
Stephan Rabanser
Stephan Günnemann
Zachary C. Lipton
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift.
2018
abs/1810.11953
CoRR
http://arxiv.org/abs/1810.11953
db/journals/corr/corr1810.html#abs-1810-11953
Richard Kurle
Stephan Günnemann
Patrick van der Smagt
Multi-Source Neural Variational Inference.
2018
abs/1811.04451
CoRR
http://arxiv.org/abs/1811.04451
db/journals/corr/corr1811.html#abs-1811-04451
Oleksandr Shchur
Maximilian Mumme
Aleksandar Bojchevski
Stephan Günnemann
Pitfalls of Graph Neural Network Evaluation.
2018
abs/1811.05868
CoRR
http://arxiv.org/abs/1811.05868
db/journals/corr/corr1811.html#abs-1811-05868
Stephan Günnemann
Machine Learning Meets Databases.
77-83
2017
17
Datenbank-Spektrum
1
https://doi.org/10.1007/s13222-017-0247-8
db/journals/dbsk/dbsk17.html#Gunnemann17
Manuel Then
Stephan Günnemann
Alfons Kemper
Thomas Neumann 0001
Efficient Batched Distance, Closeness and Betweenness Centrality Computation in Unweighted and Weighted Graphs.
169-182
2017
17
Datenbank-Spektrum
2
https://doi.org/10.1007/s13222-017-0261-x
db/journals/dbsk/dbsk17.html#ThenGKN17
Brigitte Boden
Stephan Günnemann
Holger Hoffmann
Thomas Seidl 0001
MiMAG: mining coherent subgraphs in multi-layer graphs with edge labels.
417-446
2017
50
Knowl. Inf. Syst.
2
https://doi.org/10.1007/s10115-016-0949-5
db/journals/kais/kais50.html#BodenGH017
Dhivya Eswaran
Stephan Günnemann
Christos Faloutsos
Disha Makhija
Mohit Kumar 0008
ZooBP: Belief Propagation for Heterogeneous Networks.
625-636
2017
10
Proc. VLDB Endow.
5
http://www.vldb.org/pvldb/vol10/p625-eswaran.pdf
https://doi.org/10.14778/3055540.3055554
db/journals/pvldb/pvldb10.html#EswaranGFMK17
Manuel Then
Timo Kersten
Stephan Günnemann
Alfons Kemper
Thomas Neumann 0001
Automatic Algorithm Transformation for Efficient Multi-Snapshot Analytics on Temporal Graphs.
877-888
2017
10
Proc. VLDB Endow.
8
http://www.vldb.org/pvldb/vol10/p877-then.pdf
https://doi.org/10.14778/3090163.3090166
db/journals/pvldb/pvldb10.html#ThenKGK017
Manuel Then
Stephan Günnemann
Alfons Kemper
Thomas Neumann 0001
Efficient Batched Distance and Centrality Computation in Unweighted and Weighted Graphs.
247-266
2017
BTW
conf/btw/2017
db/conf/btw/btw2017.html#ThenGK017
https://dl.gi.de/handle/20.500.12116/632
Linnea Passing
Manuel Then
Nina C. Hubig
Harald Lang
Michael Schreier
Stephan Günnemann
Alfons Kemper
Thomas Neumann 0001
SQL- and Operator-centric Data Analytics in Relational Main-Memory Databases.
84-95
2017
EDBT
https://doi.org/10.5441/002/edbt.2017.09
conf/edbt/2017
db/conf/edbt/edbt2017.html#PassingTHLSGK017
Aleksandar Bojchevski
Yves Matkovic
Stephan Günnemann
Robust Spectral Clustering for Noisy Data: Modeling Sparse Corruptions Improves Latent Embeddings.
737-746
2017
KDD
https://doi.org/10.1145/3097983.3098156
conf/kdd/2017
db/conf/kdd/kdd2017.html#BojchevskiMG17
Dhivya Eswaran
Stephan Günnemann
Christos Faloutsos
The Power of Certainty: A Dirichlet-Multinomial Model for Belief Propagation.
144-152
2017
SDM
https://doi.org/10.1137/1.9781611974973.17
conf/sdm/2017
db/conf/sdm/sdm2017.html#EswaranGF17
Nina C. Hubig
Philip Fengler
Andreas Züfle
Ruixin Yang
Stephan Günnemann
Detection and Prediction of Natural Hazards Using Large-Scale Environmental Data.
300-316
2017
SSTD
https://doi.org/10.1007/978-3-319-64367-0_16
conf/ssd/2017
db/conf/ssd/sstd2017.html#HubigFZYG17
Subhabrata Mukherjee
Stephan Günnemann
Gerhard Weikum
Personalized Item Recommendation with Continuous Experience Evolution of Users using Brownian Motion.
2017
abs/1705.02669
CoRR
http://arxiv.org/abs/1705.02669
db/journals/corr/corr1705.html#MukherjeeGW17
Aleksandar Bojchevski
Stephan Günnemann
Deep Gaussian Embedding of Attributed Graphs: Unsupervised Inductive Learning via Ranking.
2017
abs/1707.03815
CoRR
http://arxiv.org/abs/1707.03815
db/journals/corr/corr1707.html#BojchevskiG17
Stephan Rabanser
Oleksandr Shchur
Stephan Günnemann
Introduction to Tensor Decompositions and their Applications in Machine Learning.
2017
abs/1711.10781
CoRR
http://arxiv.org/abs/1711.10781
db/journals/corr/corr1711.html#abs-1711-10781
Miguel Araujo
Stephan Günnemann
Spiros Papadimitriou
Christos Faloutsos
Prithwish Basu
Ananthram Swami
Evangelos E. Papalexakis
Danai Koutra
Discovery of "comet" communities in temporal and labeled graphs Com^2.
657-677
2016
46
Knowl. Inf. Syst.
3
https://doi.org/10.1007/s10115-015-0847-2
db/journals/kais/kais46.html#AraujoGPFBSPK16
Neil Shah
Alex Beutel
Bryan Hooi
Leman Akoglu
Stephan Günnemann
Disha Makhija
Mohit Kumar 0008
Christos Faloutsos
EdgeCentric: Anomaly Detection in Edge-Attributed Networks.
327-334
2016
ICDM Workshops
https://doi.org/10.1109/ICDMW.2016.0053
https://doi.ieeecomputersociety.org/10.1109/ICDMW.2016.0053
conf/icdm/2016w
db/conf/icdm/icdm2016w.html#ShahBHAGMKF16
Saskia Metzler
Stephan Günnemann
Pauli Miettinen
Hyperbolae are No Hyperbole: Modelling Communities That are Not Cliques.
330-339
2016
ICDM
https://doi.org/10.1109/ICDM.2016.0044
https://doi.ieeecomputersociety.org/10.1109/ICDM.2016.0044
conf/icdm/2016
db/conf/icdm/icdm2016.html#MetzlerGM16
Subhabrata Mukherjee
Stephan Günnemann
Gerhard Weikum
Continuous Experience-aware Language Model.
1075-1084
2016
KDD
https://doi.org/10.1145/2939672.2939780
conf/kdd/2016
db/conf/kdd/kdd2016.html#MukherjeeGW16
Bryan Hooi
Neil Shah
Alex Beutel
Stephan Günnemann
Leman Akoglu
Mohit Kumar 0008
Disha Makhija
Christos Faloutsos
BIRDNEST: Bayesian Inference for Ratings-Fraud Detection.
495-503
2016
SDM
https://doi.org/10.1137/1.9781611974348.56
conf/sdm/2016
db/conf/sdm/sdm2016.html#HooiSBGAKMF16
Saskia Metzler
Stephan Günnemann
Pauli Miettinen
Hyperbolae Are No Hyperbole: Modelling Communities That Are Not Cliques.
2016
abs/1602.04650
CoRR
http://arxiv.org/abs/1602.04650
db/journals/corr/corr1602.html#MetzlerGM16
Emmanuel Müller
Ira Assent
Stephan Günnemann
Thomas Seidl 0001
Jennifer G. Dy
MultiClust special issue on discovering, summarizing and using multiple clusterings.
1-5
2015
98
Mach. Learn.
1-2
https://doi.org/10.1007/s10994-014-5445-0
db/journals/ml/ml98.html#MullerAG0D15
Wolfgang Gatterbauer
Stephan Günnemann
Danai Koutra
Christos Faloutsos
Linearized and Single-Pass Belief Propagation.
581-592
2015
8
Proc. VLDB Endow.
5
http://www.vldb.org/pvldb/vol8/p581-gatterbauer.pdf
https://doi.org/10.14778/2735479.2735490
db/journals/pvldb/pvldb8.html#GatterbauerGKF15
Jay Lee
Manzil Zaheer
Stephan Günnemann
Alexander J. Smola
Preferential Attachment in Graphs with Affinities.
2015
AISTATS
http://proceedings.mlr.press/v38/lee15b.html
conf/aistats/2015
db/conf/aistats/aistats2015.html#LeeZGS15
Tobias Kötter
Stephan Günnemann
Michael R. Berthold
Christos Faloutsos
Automatic Taxonomy Extraction from Bipartite Graphs.
221-230
2015
ICDM
https://doi.org/10.1109/ICDM.2015.24
https://doi.ieeecomputersociety.org/10.1109/ICDM.2015.24
conf/icdm/2015
db/conf/icdm/icdm2015.html#KotterGBF15
Manuel Then
Linnea Passing
Nina C. Hubig
Stephan Günnemann
Alfons Kemper
Thomas Neumann 0001
Effiziente Integration von Data- und Graph-Mining-Algorithmen in relationale Datenbanksysteme.
45-49
2015
LWA
https://ceur-ws.org/Vol-1458/D06_CRC47_Then.pdf
conf/lwa/2015
db/conf/lwa/lwa2015.html#ThenPHGK015
Tobias Kötter
Stephan Günnemann
Christos Faloutsos
Michael R. Berthold
Extracting Taxonomies from Bipartite Graphs.
51-52
2015
WWW (Companion Volume)
https://doi.org/10.1145/2740908.2742753
conf/www/2015c
db/conf/www/www2015c.html#KotterGFB15
Neil Shah
Alex Beutel
Bryan Hooi
Leman Akoglu
Stephan Günnemann
Disha Makhija
Mohit Kumar 0008
Christos Faloutsos
EdgeCentric: Anomaly Detection in Edge-Attributed Networks.
2015
abs/1510.05544
CoRR
http://arxiv.org/abs/1510.05544
db/journals/corr/corr1510.html#ShahBHAGMKF15
Bryan Hooi
Neil Shah
Alex Beutel
Stephan Günnemann
Leman Akoglu
Mohit Kumar 0008
Disha Makhija
Christos Faloutsos
BIRDNEST: Bayesian Inference for Ratings-Fraud Detection.
2015
abs/1511.06030
CoRR
http://arxiv.org/abs/1511.06030
db/journals/corr/corr1511.html#HooiSBGAKMF15
Stephan Günnemann
Ines Färber
Brigitte Boden
Thomas Seidl 0001
GAMer: a synthesis of subspace clustering and dense subgraph mining.
243-278
2014
40
Knowl. Inf. Syst.
2
https://doi.org/10.1007/s10115-013-0640-z
db/journals/kais/kais40.html#GunnemannFBS14
Stephan Günnemann
Ines Färber
Matthias Sebastian Rüdiger
Thomas Seidl 0001
SMVC: semi-supervised multi-view clustering in subspace projections.
253-262
2014
KDD
https://doi.org/10.1145/2623330.2623734
conf/kdd/2014
db/conf/kdd/kdd2014.html#GunnemannFRS14
Stephan Günnemann
Nikou Günnemann
Christos Faloutsos
Detecting anomalies in dynamic rating data: a robust probabilistic model for rating evolution.
841-850
2014
KDD
https://doi.org/10.1145/2623330.2623721
https://www.wikidata.org/entity/Q59551133
conf/kdd/2014
db/conf/kdd/kdd2014.html#GunnemannGF14
Miguel Araujo
Spiros Papadimitriou
Stephan Günnemann
Christos Faloutsos
Prithwish Basu
Ananthram Swami
Evangelos E. Papalexakis
Danai Koutra
Com2: Fast Automatic Discovery of Temporal ('Comet') Communities.
271-283
2014
PAKDD (2)
https://doi.org/10.1007/978-3-319-06605-9_23
https://www.wikidata.org/entity/Q59551126
conf/pakdd/2014-2
db/conf/pakdd/pakdd2014-2.html#AraujoPGFBSPK14
Tobias Kötter
Stephan Günnemann
Michael R. Berthold
Christos Faloutsos
Fault-Tolerant Concept Detection in Information Networks.
410-421
2014
PAKDD (1)
https://doi.org/10.1007/978-3-319-06608-0_34
https://www.wikidata.org/entity/Q59551145
conf/pakdd/2014-1
db/conf/pakdd/pakdd2014-1.html#KotterGBF14
Miguel Araujo
Stephan Günnemann
Gonzalo Mateos
Christos Faloutsos
Beyond Blocks: Hyperbolic Community Detection.
50-65
2014
ECML/PKDD (1)
https://doi.org/10.1007/978-3-662-44848-9_4
https://www.wikidata.org/entity/Q59551114
conf/pkdd/2014-1
db/conf/pkdd/pkdd2014-1.html#AraujoGMF14
Nikou Günnemann
Stephan Günnemann
Christos Faloutsos
Robust multivariate autoregression for anomaly detection in dynamic product ratings.
361-372
2014
WWW
https://doi.org/10.1145/2566486.2568008
https://www.wikidata.org/entity/Q59551199
conf/www/2014
db/conf/www/www2014.html#GunnemannGF14
Wolfgang Gatterbauer
Stephan Günnemann
Danai Koutra
Christos Faloutsos
Linearized and Turbo Belief Propagation.
2014
abs/1406.7288
CoRR
http://arxiv.org/abs/1406.7288
db/journals/corr/corr1406.html#GatterbauerGKF14
Stephan Günnemann
Hardy Kremer
Matthias Hannen
Thomas Seidl 0001
KDD-SC: Subspace Clustering Extensions for Knowledge Discovery Frameworks.
2014
abs/1407.3850
CoRR
http://arxiv.org/abs/1407.3850
db/journals/corr/corr1407.html#GunnemannKHS14
Stephan Günnemann
Subspace Clustering for Complex Data.
343-362
2013
BTW
https://dl.gi.de/handle/20.500.12116/17331
http://subs.emis.de/LNI/Proceedings/Proceedings214/article6852.html
conf/btw/2013
db/conf/btw/btw2013.html#Gunnemann13
Stephan Günnemann
Christos Faloutsos
Mixed Membership Subspace Clustering.
221-230
2013
ICDM
https://doi.org/10.1109/ICDM.2013.109
https://doi.ieeecomputersociety.org/10.1109/ICDM.2013.109
https://www.wikidata.org/entity/Q59551268
conf/icdm/2013
db/conf/icdm/icdm2013.html#GunnemannF13
Stephan Günnemann
Ines Färber
Sebastian Raubach
Thomas Seidl 0001
Spectral Subspace Clustering for Graphs with Feature Vectors.
231-240
2013
ICDM
https://doi.org/10.1109/ICDM.2013.110
https://doi.ieeecomputersociety.org/10.1109/ICDM.2013.110
conf/icdm/2013
db/conf/icdm/icdm2013.html#GunnemannFRS13
Hardy Kremer
Stephan Günnemann
Arne Held
Thomas Seidl 0001
An Evaluation Framework for Temporal Subspace Clustering Approaches.
1089-1092
2013
ICDM Workshops
https://doi.org/10.1109/ICDMW.2013.24
https://doi.ieeecomputersociety.org/10.1109/ICDMW.2013.24
conf/icdm/2013w
db/conf/icdm/icdmw2013.html#KremerGHS13
Jennifer H. Nguyen
Bo Hu 0012
Stephan Günnemann
Martin Ester
Finding contexts of social influence in online social networks.
1:1-1:9
2013
SNAKDD
https://doi.org/10.1145/2501025.2501028
conf/kdd/2013sna
db/conf/kdd/snakdd2013.html#NguyenHGE13
Geng Li 0002
Stephan Günnemann
Mohammed J. Zaki
Stochastic subspace search for top-k multi-view clustering.
3
2013
MultiClust@KDD
https://doi.org/10.1145/2501006.2501010
conf/multiclust/2013
db/conf/multiclust/multiclust2013.html#LiGZ13
Stephan Günnemann
Brigitte Boden
Ines Färber
Thomas Seidl 0001
Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors.
261-275
2013
PAKDD (1)
https://doi.org/10.1007/978-3-642-37453-1_22
conf/pakdd/2013-1
db/conf/pakdd/pakdd2013-1.html#GunnemannBFS13
Brigitte Boden
Stephan Günnemann
Holger Hoffmann
Thomas Seidl 0001
RMiCS: a robust approach for mining coherent subgraphs in edge-labeled multi-layer graphs.
23:1-23:12
2013
SSDBM
https://doi.org/10.1145/2484838.2484860
conf/ssdbm/2013
db/conf/ssdbm/ssdbm2013.html#BodenGHS13
Hardy Kremer
Stephan Günnemann
Simon Wollwage
Thomas Seidl 0001
Nesting the earth mover's distance for effective cluster tracing.
34:1-34:4
2013
SSDBM
https://doi.org/10.1145/2484838.2484881
conf/ssdbm/2013
db/conf/ssdbm/ssdbm2013.html#KremerGWS13
Stephan Günnemann
Subspace clustering for complex data.
2012
RWTH Aachen University
http://darwin.bth.rwth-aachen.de/opus3/volltexte/2012/4103
https://nbn-resolving.org/urn:nbn:de:hbz:82-opus-41038
https://d-nb.info/1023979101
https://d-nb.info/1025614194
Stephan Günnemann
Hardy Kremer
Charlotte Laufkötter
Thomas Seidl 0001
Tracing Evolving Subspace Clusters in Temporal Climate Data.
387-410
2012
24
Data Min. Knowl. Discov.
2
https://doi.org/10.1007/s10618-011-0237-7
db/journals/datamine/datamine24.html#GunnemannKLS12
Stephan Günnemann
Brigitte Boden
Thomas Seidl 0001
Finding density-based subspace clusters in graphs with feature vectors.
243-269
2012
25
Data Min. Knowl. Discov.
2
https://doi.org/10.1007/s10618-012-0272-z
db/journals/datamine/datamine25.html#GunnemannBS12
Brigitte Boden
Stephan Günnemann
Thomas Seidl 0001
Tracing clusters in evolving graphs with node attributes.
2331-2334
2012
CIKM
https://doi.org/10.1145/2396761.2398633
conf/cikm/2012
db/conf/cikm/cikm2012.html#BodenGS12
Emmanuel Müller
Stephan Günnemann
Ines Färber
Thomas Seidl 0001
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data.
1207-1210
2012
ICDE
https://doi.org/10.1109/ICDE.2012.142
https://doi.ieeecomputersociety.org/10.1109/ICDE.2012.142
conf/icde/2012
db/conf/icde/icde2012.html#MullerGFS12
Stephan Günnemann
Phuong Dao
Mohsen Jamali
Martin Ester
Assessing the Significance of Data Mining Results on Graphs with Feature Vectors.
270-279
2012
ICDM
https://doi.org/10.1109/ICDM.2012.70
https://doi.ieeecomputersociety.org/10.1109/ICDM.2012.70
conf/icdm/2012
db/conf/icdm/icdm2012.html#GunnemannDJE12
Hardy Kremer
Stephan Günnemann
Arne Held
Thomas Seidl 0001
Effective and Robust Mining of Temporal Subspace Clusters.
369-378
2012
ICDM
https://doi.org/10.1109/ICDM.2012.44
https://doi.ieeecomputersociety.org/10.1109/ICDM.2012.44
conf/icdm/2012
db/conf/icdm/icdm2012.html#KremerGHS12
Stephan Günnemann
Hardy Kremer
Richard Musiol
Roman Haag
Thomas Seidl 0001
A Subspace Clustering Extension for the KNIME Data Mining Framework.
886-889
2012
ICDM Workshops
https://doi.org/10.1109/ICDMW.2012.31
https://doi.ieeecomputersociety.org/10.1109/ICDMW.2012.31
conf/icdm/2012w
db/conf/icdm/icdmw2012.html#GunnemannKMHS12
Stephan Günnemann
Ines Färber
Thomas Seidl 0001
Multi-view clustering using mixture models in subspace projections.
132-140
2012
KDD
https://doi.org/10.1145/2339530.2339553
conf/kdd/2012
db/conf/kdd/kdd2012.html#GunnemannFS12
Stephan Günnemann
Ines Färber
Kittipat Virochsiri
Thomas Seidl 0001
Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data.
352-360
2012
KDD
https://doi.org/10.1145/2339530.2339588
conf/kdd/2012
db/conf/kdd/kdd2012.html#GunnemannFVS12
Brigitte Boden
Stephan Günnemann
Holger Hoffmann
Thomas Seidl 0001
Mining coherent subgraphs in multi-layer graphs with edge labels.
1258-1266
2012
KDD
https://doi.org/10.1145/2339530.2339726
conf/kdd/2012
db/conf/kdd/kdd2012.html#BodenGHS12
Hardy Kremer
Stephan Günnemann
Arne Held
Thomas Seidl 0001
Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases.
444-455
2012
PAKDD (1)
https://doi.org/10.1007/978-3-642-30217-6_37
conf/pakdd/2012-1
db/conf/pakdd/pakdd2012-1.html#KremerGHS12
Stephan Günnemann
Brigitte Boden
Thomas Seidl 0001
Substructure Clustering: A Novel Mining Paradigm for Arbitrary Data Types.
280-297
2012
SSDBM
https://doi.org/10.1007/978-3-642-31235-9_19
conf/ssdbm/2012
db/conf/ssdbm/ssdbm2012.html#GunnemannBS12
Emmanuel Müller
Ira Assent
Stephan Günnemann
Patrick Gerwert
Matthias Hannen
Timm Jansen
Thomas Seidl 0001
A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional Databases.
347-366
2011
BTW
conf/btw/2011
db/conf/btw/btw2011.html#MullerAGGHJS09
https://dl.gi.de/handle/20.500.12116/19588
http://subs.emis.de/LNI/Proceedings/Proceedings180/article44.html
Emmanuel Müller
Ira Assent
Stephan Günnemann
Thomas Seidl 0001
Scalable density-based subspace clustering.
1077-1086
2011
CIKM
https://doi.org/10.1145/2063576.2063733
conf/cikm/2011
db/conf/cikm/cikm2011.html#MullerAGS11
Stephan Günnemann
Ines Färber
Emmanuel Müller
Ira Assent
Thomas Seidl 0001
External evaluation measures for subspace clustering.
1363-1372
2011
CIKM
https://doi.org/10.1145/2063576.2063774
conf/cikm/2011
db/conf/cikm/cikm2011.html#GunnemannFMAS11
Stephan Günnemann
Hardy Kremer
Dominik Lenhard
Thomas Seidl 0001
Subspace clustering for indexing high dimensional data: a main memory index based on local reductions and individual multi-representations.
237-248
2011
EDBT
https://doi.org/10.1145/1951365.1951395
conf/edbt/2011
db/conf/edbt/edbt2011.html#GunnemannKLS11
Stephan Günnemann
Emmanuel Müller
Sebastian Raubach
Thomas Seidl 0001
Flexible Fault Tolerant Subspace Clustering for Data with Missing Values.
231-240
2011
ICDM
https://doi.org/10.1109/ICDM.2011.70
https://doi.ieeecomputersociety.org/10.1109/ICDM.2011.70
conf/icdm/2011
db/conf/icdm/icdm2011.html#GunnemannMRS11
Stephan Günnemann
Brigitte Boden
Thomas Seidl 0001
Finding Density-Based Subspace Clusters in Graphs with Feature Vectors.
20-27
2011
LWA
conf/lwa/2011
db/conf/lwa/lwa2011.html#GunnemannB011
Stephan Günnemann
Hardy Kremer
Charlotte Laufkötter
Thomas Seidl 0001
Tracing Evolving Clusters by Subspace and Value Similarity.
444-456
2011
PAKDD (2)
https://doi.org/10.1007/978-3-642-20847-8_37
conf/pakdd/2011-2
db/conf/pakdd/pakdd2011-2.html#GunnemannKLS11
Stephan Günnemann
Brigitte Boden
Thomas Seidl 0001
DB-CSC: A Density-Based Approach for Subspace Clustering in Graphs with Feature Vectors.
565-580
2011
ECML/PKDD (1)
https://doi.org/10.1007/978-3-642-23780-5_46
conf/pkdd/2011-1
db/conf/pkdd/pkdd2011-1.html#GunnemannBS11
Hardy Kremer
Stephan Günnemann
Anca Maria Ivanescu
Ira Assent
Thomas Seidl 0001
Efficient Processing of Multiple DTW Queries in Time Series Databases.
150-167
2011
SSDBM
https://doi.org/10.1007/978-3-642-22351-8_9
conf/ssdbm/2011
db/conf/ssdbm/ssdbm2011.html#KremerGIAS11
Emmanuel Müller
Stephan Günnemann
Ira Assent
Thomas Seidl 0001
Proceedings of the 2nd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings, Athens, Greece, September 5, 2011, in conjunction with ECML/PKDD 2011
CEUR-WS.org
CEUR Workshop Proceedings
772
2011
https://ceur-ws.org/Vol-772
https://nbn-resolving.org/urn:nbn:de:0074-772-4
MultiClust@ECML/PKDD
db/conf/multiclust/multiclust2011.html
Stephan Günnemann
Ines Färber
Hardy Kremer
Thomas Seidl 0001
CoDA: Interactive Cluster Based Concept Discovery.
1633-1636
2010
3
Proc. VLDB Endow.
2
http://www.vldb.org/pvldb/vldb2010/pvldb_vol3/D30.pdf
https://doi.org/10.14778/1920841.1921058
db/journals/pvldb/pvldb3.html#GunnemannFKS10
Ira Assent
Hardy Kremer
Stephan Günnemann
Thomas Seidl 0001
Pattern detector: fast detection of suspicious stream patterns for immediate reaction.
709-712
2010
EDBT
https://doi.org/10.1145/1739041.1739133
conf/edbt/2010
db/conf/edbt/edbt2010.html#AssentKGS10
Hardy Kremer
Stephan Günnemann
Thomas Seidl 0001
Detecting Climate Change in Multivariate Time Series Data by Novel Clustering and Cluster Tracing Techniques.
96-97
2010
ICDM Workshops
https://doi.org/10.1109/ICDMW.2010.39
https://doi.ieeecomputersociety.org/10.1109/ICDMW.2010.39
conf/icdm/2010w
db/conf/icdm/icdmw2010.html#KremerGS10
Stephan Günnemann
Ines Färber
Brigitte Boden
Thomas Seidl 0001
Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two Paradigms.
845-850
2010
ICDM
https://doi.org/10.1109/ICDM.2010.95
https://doi.ieeecomputersociety.org/10.1109/ICDM.2010.95
conf/icdm/2010
db/conf/icdm/icdm2010.html#GunnemannFBS10
Emmanuel Müller
Stephan Günnemann
Ines Färber
Thomas Seidl 0001
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data.
1220
2010
ICDM
https://doi.org/10.1109/ICDM.2010.85
https://doi.ieeecomputersociety.org/10.1109/ICDM.2010.85
conf/icdm/2010
db/conf/icdm/icdm2010.html#MullerGFS10
Stephan Günnemann
Hardy Kremer
Ines Färber
Thomas Seidl 0001
MCExplorer: Interactive Exploration of Multiple (Subspace) Clustering Solutions.
1387-1390
2010
ICDM Workshops
https://doi.org/10.1109/ICDMW.2010.29
https://doi.ieeecomputersociety.org/10.1109/ICDMW.2010.29
conf/icdm/2010w
db/conf/icdm/icdmw2010.html#GunnemannKFS10
Stephan Günnemann
Thomas Seidl 0001
Subgraph Mining on Directed and Weighted Graphs.
133-146
2010
PAKDD (2)
https://doi.org/10.1007/978-3-642-13672-6_14
conf/pakdd/2010-2
db/conf/pakdd/pakdd2010-2.html#GunnemannS10
Stephan Günnemann
Hardy Kremer
Thomas Seidl 0001
Subspace Clustering for Uncertain Data.
385-396
2010
SDM
https://doi.org/10.1137/1.9781611972801.34
conf/sdm/2010
db/conf/sdm/sdm2010.html#GunnemannKS10
Philipp Kranen
Stephan Günnemann
Sergej Fries
Thomas Seidl 0001
MC-Tree: Improving Bayesian Anytime Classification.
252-269
2010
SSDBM
https://doi.org/10.1007/978-3-642-13818-8_19
conf/ssdbm/2010
db/conf/ssdbm/ssdbm2010.html#KranenGFS10
Emmanuel Müller
Stephan Günnemann
Ira Assent
Thomas Seidl 0001
Evaluating Clustering in Subspace Projections of High Dimensional Data.
1270-1281
2009
2
Proc. VLDB Endow.
1
http://www.vldb.org/pvldb/vol2/vldb09-600.pdf
https://doi.org/10.14778/1687627.1687770
db/journals/pvldb/pvldb2.html#MullerGAS09
Ira Assent
Stephan Günnemann
Hardy Kremer
Thomas Seidl 0001
High-Dimensional Indexing for Multimedia Features.
187-206
2009
BTW
conf/btw/2009
db/conf/btw/btw2009.html#AssentGKS09
https://dl.gi.de/handle/20.500.12116/20444
http://subs.emis.de/LNI/Proceedings/Proceedings144/article4647.html
Stephan Günnemann
Emmanuel Müller
Ines Färber
Thomas Seidl 0001
Detection of orthogonal concepts in subspaces of high dimensional data.
1317-1326
2009
CIKM
https://doi.org/10.1145/1645953.1646120
conf/cikm/2009
db/conf/cikm/cikm2009.html#GunnemannMFS09
Emmanuel Müller
Ira Assent
Stephan Günnemann
Ralph Krieger
Thomas Seidl 0001
Relevant Subspace Clustering: Mining the Most Interesting Non-redundant Concepts in High Dimensional Data.
377-386
2009
ICDM
https://doi.org/10.1109/ICDM.2009.10
https://doi.ieeecomputersociety.org/10.1109/ICDM.2009.10
conf/icdm/2009
db/conf/icdm/icdm2009.html#MullerAGKS09
Emmanuel Müller
Ira Assent
Ralph Krieger
Stephan Günnemann
Thomas Seidl 0001
DensEst: Density Estimation for Data Mining in High Dimensional Spaces.
175-186
2009
SDM
https://doi.org/10.1137/1.9781611972795.16
conf/sdm/2009
db/conf/sdm/sdm2009.html#MullerAKGS09
M. H. I. Abdalla
Ahmad Abu-Akel
Keir Adams
Amir Akbarnejad
Leman Akoglu
Roberto Alonso
Anima Anandkumar
Eugenio Angriman
Miguel Araujo
Alán Aspuru-Guzik
Ira Assent
Matan Atad
Martin AtzmüllerMartin Atzmueller
Francois-Xavier AubetFrançois-Xavier Aubet
Morgane Ayle
Kamyar Azizzadenesheli
Atta Badii
Bernard Bäker
Regina Barzilay
Prithwish Basu
Dominique Beaini
Florian Becker
Erik J. Bekkers
Michael R. Berthold
Alex Beutel
Emmanuel de Bézenac
Tijl De Bie
Marin Bilos
Bernd Bischl
Sebastian Bischoff 0001
Martin Blais
Brigitte Boden
Montgomery Bohde
Simon Böhm
Aleksandar Bojchevski
Oliver Borchert
Michael M. Bronstein
Matthias Bungeroth
Charlotte Bunne
Paul Büschl
Francesco Campi
Michele Catasta
A. Taylan CemgilAli Taylan Cemgil
Moharram Challenger
Bertrand Charpentier
Connor W. Coley
Gabriele Corso
Botond Cseke
Ameya Daigavane
Christian Dallago
Phuong Dao
Abhishek Das
Deepan Das
Rayen Dhahri
Codrut-Andrei Diaconu
David Dobre
Yuanqi Du
Maximilian Durner
Jennifer G. Dy
Carl Edwards
Dirk Eilers
Sven Elflein
Ege Erdogan
Stefano Ermon
Ali Ertürk
Martin Ester
Dhivya Eswaran
Ivan Ezhov
Christos Faloutsos
Ada Fang
Ines Färber
Mohamed Farghal
Jianxiang Feng
Philip Fengler
Valentin Flunkert
Vincent Fortuin
Nicola Franco
Fabrizio Frasca
Sergej Fries
Cong Fu 0003
Tianfan Fu
Xiang Fu 0005
Nicholas Gao
Johannes GasteigerJohannes Klicpera
Jan Gasthaus
Wolfgang Gatterbauer
Simon Geisler
Sascha Geringer
Patrick Gerwert
Johannes Getzner
Gauthier Gidel
Francesco Di Giovanni
Sandhya Giri
Shankari Giri
Lukas Gosch
Alexander van der Grinten
Martin Grohe
Janek Groß
Filippo Guerranti
Shurui Gui
Nikou Günnemann
Florian Gyrock
Roman Haag
Tom Haider
Zhen Han
Matthias Hannen
Jan Hansen-Palmus
Julius Hansjakob
Nick Harmening
Arne Held
Jacob Helwig
Maximilian Henne
Leon Hetzel
Thomas Heyenbrock
Marcel Hildebrandt
Holger Hoffmann
Elyssa F. Hofgard
Bryan Hooi
Michael E. Houle
Bo Hu 0012
Qian Huang
Nina C. Hubig
Alexander Immer
Tommi S. Jaakkola
Martin Jaggi
Mohsen Jamali
Timm Jansen
Tim Januschowski
Stefanie Jegelka
Heng Ji
Shuiwang Ji
Meng Jiang 0001
Chaitanya K. Joshi
Eduard Jundt
Georgios Kaissis
Rafiq Kamel
Amol Kapoor
Alfons Kemper
Timo Kersten
Mohamed Amine Ketata
Simon Kibler
Niki Kilbertus
Jörg Christian Kirchhof
Tobias Kirschstein
Gudrun Klinker
Alexej Klushyn
Daniel Knobloch
Mykel J. Kochenderfer
Marcel Kollovieh
Rajat Koner
Anna-Kathrin Kopetzki
Daniel Korth
Arthur Kosmala
Tobias Kötter
Danai Koutra
Philipp Kranen
Hardy Kremer
Ralph Krieger
Jonathan Külz
Daniel Külzer
Mohit Kumar 0008
Richard Kurle
Jerry Kurtin
Evgeny Kusmenko
Gitta Kutyniok
Aleksei Kuvshinov
Adriana Ladera
Harald Lang
Charlotte Laufkötter
Hannah Lawrence
Jay Lee
Jongseok Lee
Richard Leibrandt
Dominik Lenhard
Jure Leskovec
Ron Levie
Geng Li 0002
Hang Li 0010
Hong Li
Xiner Li
Yujia Li
Marten Lienen
Jefrey Lijffijt
Hao Lin 0002
Yuchao Lin
Hongyi Ling
Pietro LiòPietro Lió
Zachary C. Lipton
Or Litany
Gang Liu 0025
Hongfu Liu 0001
Meng Liu
Yi Liu 0059
Jeanette Miriam Lorenz
Mohammad Lotfollahi
David Lüdke
Michal Lukasik
Alexandra Lungu
Youzhi Luo
Yunpu Ma
Disha Makhija
Daniel J. Mankowitz
Alexandru MaraAlexandru Cristian Mara
Johannes T. Margraf
Gonzalo Mateos
Simon V. Mathis
Andrea Matic-FlierlAndrea Matic
Yves Matkovic
Julian McGinnis
Bjoern H. Menze
Saskia Metzler
Henning Meyerhenke
Pauli Miettinen
Andrei Mituca
Armin Moin
Federico Monti
Christopher Morris 0001
Barbara Moser
Artur Mrowca
Felix Mujkanovic
Subhabrata Mukherjee
Emmanuel Müller
Maximilian Mumme
Richard Musiol
Florian Naumann
Thomas Neumann 0001
Yuriy Nevmyvaka
Jennifer H. Nguyen
Tam Thanh Nguyen
Xiangyu Ning
Martin Nocker
Cosmin Paduraru
Johannes C. Paetzold
Raffaele Paolino
Spiros Papadimitriou
Evangelos E. Papalexakis
Theodore Papamarkou
Linnea Passing
Bryan Perozzi
Tuong Phung
Michael Plainer
Benedikt Poggel
Chinmay Prabhakar
Chendi Qian
Xiaofeng Qian
Xiaoning Qian
Stephan Rabanser
John Rachwan
Emanuel Ramneantu
Syama Sundar Rangapuram
Hassan Rasheed
Kashif Rasul
Sebastian Raubach
Bastian Rieck
Lorenzo von Ritter
Jonas Ritz
Ismael Rodríguez
Karsten Roscher
Emanuele Rossi
Stephan Rössler
Felippe Schmoeller RozaFelippe Schmoeller da Roza
Benedek RozemberczkiBenedek Rózemberczki
Matthias Sebastian Rüdiger
David Rügamer
Bernhard Rumpe
Vitalii Rusinov
Yusuf Saber
Sudipan Saha
David Salinas
Victor Garcia Satorras
Alexandra Saxton
Marouane Sayih
Sebastian Schmidt 0006
Tobias Schmidt
Anderson Schneider
Yan Scholten
Michael Schreier
Matthias Schubert
Jan Schuchardt
Maximilian E. Schüle
Franziska Schwaiger
Leo Schwinn
Thomas Seidl 0001
Anjany Sekuboyina
Ransalu Senanayake
Neil Shah
Marawan Shalaby
Oleksandr Shchur
Suprosanna Shit
Muhammed Shuaibi
Frédéric Simonis
Poulami Sinhamahapatra
Hakan Sirin
Patrick van der Smagt
Tess E. Smidt
Alexander J. Smola
Johanna Sommer
Andreas Spitz
Maximilian Springer
Anuroop Sriram
Maximilian Stadler
Hannes Stärk
Anna Starovoit
Sebastian Steinhorst
Sebastian U. Stich
Sina Stocker
Alex Strasser
Daniel Sturm 0002
Jan Stutzki
Peter Súkeník
Jimeng Sun 0001
Ananthram Swami
Aria Mansouri Tehrani
Fabian J. Theis
Manuel Then
Kevin Kennard Thiel
Mihail I. Todorov
Prudencio Tossou
Volker Tresp
Rudolph Triebel
Ali Caner Türkmen
Zachary W. Ulissi
Elen Vardanyan
Kittipat Virochsiri
Peter Vogel
Dimitri Vorona
Limei Wang
Rui Wang 0086
Yucheng Wang
Yuyi Wang 0001
Ukrit Wattanavaekin
Gerhard Weikum
Maurice Weiler
Stefan Weißenberger
Robert West 0001
Jonas Gregor Wiese
Lisa Wimmer
Peter Wolf
Tom Wollschläger
Simon Wollwage
Junjie Wu 0002
Tailin Wu
Yihan Wu
Sophie Xhonneux
Yaochen Xie
Yuqing Xie 0006
Minkai Xu
Shenglong Xu
Zhao Xu 0005
Keqiang Yan
Ruixin Yang
Chandan Yeshwanth
Zinuo Yi
Haiyang Yu
Rose Yu
Manzil Zaheer
Mohammed J. Zaki
Chenxiang Zhang
Xuan Zhang
Tong Zhao 0003
Xiaoxiang Zhu 0001Xiao Xiang Zhu 0001
Alexander Ziller
Anca Maria ZimmerAnca Maria Ivanescu
Albrecht Zimmermann
C. Lawrence Zitnick
Marinka Zitnik
Andreas Züfle
Daniel Zügner