Giovanni Montana
Alex Beeson
Giovanni Montana
Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning.
443-488
2024
January
113
Mach. Learn.
1
https://doi.org/10.1007/s10994-023-06458-y
db/journals/ml/ml113.html#BeesonM24
Charles A. Hepburn
Giovanni Montana
Model-based trajectory stitching for improved behavioural cloning and its applications.
647-674
2024
February
113
Mach. Learn.
2
https://doi.org/10.1007/s10994-023-06392-z
db/journals/ml/ml113.html#HepburnM24
David Ireland
Giovanni Montana
REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes.
2024
abs/2401.08850
CoRR
https://doi.org/10.48550/arXiv.2401.08850
db/journals/corr/corr2401.html#abs-2401-08850
Emanuele Pesce
Giovanni Montana
Learning multi-agent coordination through connectivity-driven communication.
483-514
2023
February
112
Mach. Learn.
2
https://doi.org/10.1007/s10994-022-06286-6
db/journals/ml/ml112.html#PesceM23
Adam R. Brentnall
Emma C. Atakpa
Harry Hill
Ruggiero Santeramo
Celeste Damiani
Jack Cuzick
Giovanni Montana
Stephen W. Duffy
An optimization framework to guide the choice of thresholds for risk-based cancer screening.
2023
6
npj Digit. Medicine
https://doi.org/10.1038/s41746-023-00967-9
db/journals/npjdm/npjdm6.html#BrentnallAHSDCMD23
Mingqi Gao 0003
Jungong Han
Feng Zheng
James J. Q. Yu
Giovanni Montana
Video Object Segmentation using Point-based Memory Network.
109073
2023
134
Pattern Recognit.
https://doi.org/10.1016/j.patcog.2022.109073
db/journals/pr/pr134.html#GaoHZYM23
Mingqi Gao 0003
Jinyu Yang
Jungong Han
Ke Lu
Feng Zheng
Giovanni Montana
Decoupling Multimodal Transformers for Referring Video Object Segmentation.
4518-4528
2023
September
33
IEEE Trans. Circuits Syst. Video Technol.
9
https://doi.org/10.1109/TCSVT.2023.3284979
db/journals/tcsv/tcsv33.html#GaoYHLZM23
Nick Byrne
James R. Clough
Israel Valverde
Giovanni Montana
Andrew P. King
A Persistent Homology-Based Topological Loss for CNN-Based Multiclass Segmentation of CMR.
3-14
2023
42
IEEE Trans. Medical Imaging
1
https://doi.org/10.1109/TMI.2022.3203309
db/journals/tmi/tmi42.html#ByrneCVMK23
George Watkins
Giovanni Montana
Jürgen Branke
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks.
491-505
2023
LION
https://doi.org/10.1007/978-3-031-44505-7_33
conf/lion/2023
db/conf/lion/lion2023.html#WatkinsMB23
Mianchu Wang
Yue Jin
Giovanni Montana
Goal-conditioned Offline Reinforcement Learning through State Space Partitioning.
2023
abs/2303.09367
CoRR
https://doi.org/10.48550/arXiv.2303.09367
db/journals/corr/corr2303.html#abs-2303-09367
Alex Beeson
Giovanni Montana
Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning.
2023
abs/2303.14716
CoRR
https://doi.org/10.48550/arXiv.2303.14716
db/journals/corr/corr2303.html#abs-2303-14716
George Watkins
Giovanni Montana
Jürgen Branke
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks.
2023
abs/2304.04051
CoRR
https://doi.org/10.48550/arXiv.2304.04051
db/journals/corr/corr2304.html#abs-2304-04051
Ozsel Kilinc
Giovanni Montana
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations.
465-486
2022
111
Mach. Learn.
2
https://doi.org/10.1007/s10994-021-06116-1
db/journals/ml/ml111.html#KilincM22
David Ireland
Giovanni Montana
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation.
9622-9638
2022
ICML
https://proceedings.mlr.press/v162/ireland22a.html
conf/icml/2022
db/conf/icml/icml2022.html#IrelandM22
Matthew MacPherson
Keerthini Muthuswamy
Ashik Amlani
Charles Hutchinson
Vicky Goh
Giovanni Montana
Assessing the Performance of Automated Prediction and Ranking of Patient Age from Chest X-rays Against Clinicians.
255-265
2022
MICCAI (8)
https://doi.org/10.1007/978-3-031-16449-1_25
conf/miccai/2022-7
db/conf/miccai/miccai2022-7.html#MacPhersonMAHGM22
David Ireland
Giovanni Montana
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation.
2022
abs/2205.10106
CoRR
https://doi.org/10.48550/arXiv.2205.10106
db/journals/corr/corr2205.html#abs-2205-10106
Matthew MacPherson
Keerthini Muthuswamy
Ashik Amlani
Charles Hutchinson
Vicky Goh
Giovanni Montana
Assessing the Performance of Automated Prediction and Ranking of Patient Age from Chest X-rays Against Clinicians.
2022
abs/2207.01302
CoRR
https://doi.org/10.48550/arXiv.2207.01302
db/journals/corr/corr2207.html#abs-2207-01302
Charles A. Hepburn
Giovanni Montana
Model-based Trajectory Stitching for Improved Offline Reinforcement Learning.
2022
abs/2211.11603
CoRR
https://doi.org/10.48550/arXiv.2211.11603
db/journals/corr/corr2211.html#abs-2211-11603
Alex Beeson
Giovanni Montana
Improving TD3-BC: Relaxed Policy Constraint for Offline Learning and Stable Online Fine-Tuning.
2022
abs/2211.11802
CoRR
https://doi.org/10.48550/arXiv.2211.11802
db/journals/corr/corr2211.html#abs-2211-11802
Charles A. Hepburn
Giovanni Montana
Model-based trajectory stitching for improved behavioural cloning and its applications.
2022
abs/2212.04280
CoRR
https://doi.org/10.48550/arXiv.2212.04280
db/journals/corr/corr2212.html#abs-2212-04280
Henry Charlesworth
Giovanni Montana
Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning.
1496-1506
2021
ICML
http://proceedings.mlr.press/v139/charlesworth21a.html
conf/icml/2021
db/conf/icml/icml2021.html#CharlesworthM21
Aydan Gasimova
Giovanni Montana
Daniel Rueckert
Automated Knee X-ray Report Generation.
2021
abs/2105.10702
CoRR
https://arxiv.org/abs/2105.10702
db/journals/corr/corr2105.html#abs-2105-10702
Nick Byrne
James R. Clough
Isra Valverde
Giovanni Montana
Andrew P. King
A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR.
2021
abs/2107.12689
CoRR
https://arxiv.org/abs/2107.12689
db/journals/corr/corr2107.html#abs-2107-12689
Emanuele Pesce
Giovanni Montana
Improving coordination in small-scale multi-agent deep reinforcement learning through memory-driven communication.
1727-1747
2020
109
Mach. Learn.
9-10
https://doi.org/10.1007/s10994-019-05864-5
db/journals/ml/ml109.html#PesceM20
Nicoló Savioli
Enrico Grisan
Silvia Visentin
Erich Cosmi
Giovanni Montana
Pablo Lamata
Real-time diameter of the fetal aorta from ultrasound.
6735-6744
2020
32
Neural Comput. Appl.
11
https://doi.org/10.1007/s00521-019-04646-3
https://www.wikidata.org/entity/Q96303895
db/journals/nca/nca32.html#SavioliGVCML20
Nick Byrne
James R. Clough
Giovanni Montana
Andrew P. King
A Persistent Homology-Based Topological Loss Function for Multi-class CNN Segmentation of Cardiac MRI.
3-13
2020
M&Ms and EMIDEC/STACOM@MICCAI
https://doi.org/10.1007/978-3-030-68107-4_1
conf/miccai/2020emidec
db/conf/miccai/emidec2020.html#ByrneCMK20
Ksenia Sokolova
Gareth J. Barker
Giovanni Montana
Convolutional neural-network-based ordinal regression for brain age prediction from MRI scans.
113132B
2020
Medical Imaging: Image Processing
https://doi.org/10.1117/12.2549636
conf/miip/2020
db/conf/miip/miip2020.html#SokolovaBM20
Henry Charlesworth
Giovanni Montana
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals.
2020
NeurIPS
https://proceedings.neurips.cc/paper/2020/hash/6101903146e4bbf4999c449d78441606-Abstract.html
conf/nips/2020
db/conf/nips/neurips2020.html#CharlesworthM20
Emanuele Pesce
Giovanni Montana
Connectivity-driven Communication in Multi-agent Reinforcement Learning through Diffusion Processes on Graphs.
2020
abs/2002.05233
CoRR
https://arxiv.org/abs/2002.05233
db/journals/corr/corr2002.html#abs-2002-05233
Saad Mohamad
Giovanni Montana
Adaptive Experience Selection for Policy Gradient.
2020
abs/2002.06946
CoRR
https://arxiv.org/abs/2002.06946
db/journals/corr/corr2002.html#abs-2002-06946
Henry Charlesworth
Giovanni Montana
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals.
2020
abs/2006.00900
CoRR
https://arxiv.org/abs/2006.00900
db/journals/corr/corr2006.html#abs-2006-00900
Ozsel Kilinc
Giovanni Montana
Follow the Object: Curriculum Learning for Manipulation Tasks with Imagined Goals.
2020
abs/2008.02066
CoRR
https://arxiv.org/abs/2008.02066
db/journals/corr/corr2008.html#abs-2008-02066
Nick Byrne
James R. Clough
Giovanni Montana
Andrew P. King
A persistent homology-based topological loss function for multi-class CNN segmentation of cardiac MRI.
2020
abs/2008.09585
CoRR
https://arxiv.org/abs/2008.09585
db/journals/corr/corr2008.html#abs-2008-09585
Henry Charlesworth
Giovanni Montana
Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning.
2020
abs/2009.05104
CoRR
https://arxiv.org/abs/2009.05104
db/journals/corr/corr2009.html#abs-2009-05104
Emanuele Pesce
Samuel Withey
Petros-Pavlos Ypsilantis
Robert Bakewell
Vicky Goh
Giovanni Montana
Learning to detect chest radiographs containing pulmonary lesions using visual attention networks.
26-38
2019
53
Medical Image Anal.
https://doi.org/10.1016/j.media.2018.12.007
https://www.wikidata.org/entity/Q91125516
db/journals/mia/mia53.html#PesceWYBGM19
Briti Gangopadhyay
Siddartha Khastgir
Sumanta Dey
Pallab Dasgupta
Giovanni Montana
Paul A. Jennings
Identification of Test Cases for Automated Driving Systems Using Bayesian Optimization.
1961-1967
2019
ITSC
https://doi.org/10.1109/ITSC.2019.8917103
conf/itsc/2019
db/conf/itsc/itsc2019.html#GangopadhyayKDD19
Nick Byrne
James R. Clough
Isra Valverde
Giovanni Montana
Andrew P. King
Topology-Preserving Augmentation for CNN-Based Segmentation of Congenital Heart Defects from 3D Paediatric CMR.
181-188
2019
SUSI/PIPPI@MICCAI
https://doi.org/10.1007/978-3-030-32875-7_20
conf/miccai/2019susi
db/conf/miccai/susi2019.html#ByrneCVMK19
Emanuele Pesce
Giovanni Montana
Improving Coordination in Multi-Agent Deep Reinforcement Learning through Memory-driven Communication.
2019
abs/1901.03887
CoRR
http://arxiv.org/abs/1901.03887
db/journals/corr/corr1901.html#abs-1901-03887
Zhana Kuncheva
Giovanni Montana
Spectral Multi-scale Community Detection in Temporal Networks with an Application.
2019
abs/1901.10521
CoRR
http://arxiv.org/abs/1901.10521
db/journals/corr/corr1901.html#abs-1901-10521
Yang Hu
Giovanni Montana
Skill Transfer in Deep Reinforcement Learning under Morphological Heterogeneity.
2019
abs/1908.05265
CoRR
http://arxiv.org/abs/1908.05265
db/journals/corr/corr1908.html#abs-1908-05265
Nick Byrne
James R. Clough
Isra Valverde
Giovanni Montana
Andrew P. King
Topology-preserving augmentation for CNN-based segmentation of congenital heart defects from 3D paediatric CMR.
2019
abs/1908.08870
CoRR
http://arxiv.org/abs/1908.08870
db/journals/corr/corr1908.html#abs-1908-08870
Ozsel Kilinc
Yang Hu
Giovanni Montana
Reinforcement Learning for Robotic Manipulation using Simulated Locomotion Demonstrations.
2019
abs/1910.07294
CoRR
http://arxiv.org/abs/1910.07294
db/journals/corr/corr1910.html#abs-1910-07294
Dimosthenis Tsagkrasoulis
Giovanni Montana
Random forest regression for manifold-valued responses.
6-13
2018
101
Pattern Recognit. Lett.
https://doi.org/10.1016/j.patrec.2017.11.008
db/journals/prl/prl101.html#TsagkrasoulisM18
Ricardo Pio Monti
Christoforos Anagnostopoulos
Giovanni Montana
Adaptive regularization for Lasso models in the context of nonstationary data streams.
237-247
2018
11
Stat. Anal. Data Min.
5
https://doi.org/10.1002/sam.11390
db/journals/sadm/sadm11.html#MontiAM18
Nicoló Savioli
Silvia Visentin
Erich Cosmi
Enrico Grisan
Pablo Lamata
Giovanni Montana
Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound.
148-157
2018
ICANN (2)
https://doi.org/10.1007/978-3-030-01421-6_15
conf/icann/2018-2
db/conf/icann/icann2018-2.html#SavioliVCGLM18
Nicoló Savioli
Giovanni Montana
Pablo Lamata
V-FCNN: Volumetric Fully Convolution Neural Network for Automatic Atrial Segmentation.
273-281
2018
STACOM@MICCAI
https://doi.org/10.1007/978-3-030-12029-0_30
conf/miccai/2018stacom
db/conf/miccai/stacom2018.html#SavioliML18
Ruggiero Santeramo
Samuel Withey
Giovanni Montana
Longitudinal Detection of Radiological Abnormalities with Time-Modulated LSTM.
326-333
2018
DLMIA/ML-CDS@MICCAI
https://doi.org/10.1007/978-3-030-00889-5_37
conf/miccai/2018dlmia
db/conf/miccai/dlmia2018.html#SanteramoWM18
Mauro Annarumma
Giovanni Montana
Deep metric learning for multi-labelled radiographs.
34-37
2018
SAC
https://doi.org/10.1145/3167132.3167379
conf/sac/2018
db/conf/sac/sac2018.html#AnnarummaM18
Nicoló Savioli
Miguel Silva Vieira
Pablo Lamata
Giovanni Montana
Automated Segmentation on the Entire Cardiac Cycle Using a Deep Learning Work - Flow.
153-158
2018
SNAMS
https://doi.org/10.1109/SNAMS.2018.8554962
conf/snams/2018
db/conf/snams/snams2018.html#SavioliVLM18
Nicoló Savioli
Silvia Visentin
Erich Cosmi
Enrico Grisan
Pablo Lamata
Giovanni Montana
Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound.
2018
abs/1807.04056
CoRR
http://arxiv.org/abs/1807.04056
db/journals/corr/corr1807.html#abs-1807-04056
Ruggiero Santeramo
Samuel Withey
Giovanni Montana
Longitudinal detection of radiological abnormalities with time-modulated LSTM.
2018
abs/1807.06144
CoRR
http://arxiv.org/abs/1807.06144
db/journals/corr/corr1807.html#abs-1807-06144
Nicoló Savioli
Giovanni Montana
Pablo Lamata
V-FCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial Segmentation.
2018
abs/1808.01944
CoRR
http://arxiv.org/abs/1808.01944
db/journals/corr/corr1808.html#abs-1808-01944
Nicoló Savioli
Miguel S. Vieira
Pablo Lamata
Giovanni Montana
Automated segmentation on the entire cardiac cycle using a deep learning work-flow.
2018
abs/1809.01015
CoRR
http://arxiv.org/abs/1809.01015
db/journals/corr/corr1809.html#abs-1809-01015
Nicoló Savioli
Miguel Silva Vieira
Pablo Lamata
Giovanni Montana
A Generative Adversarial Model for Right Ventricle Segmentation.
2018
abs/1810.03969
CoRR
http://arxiv.org/abs/1810.03969
db/journals/corr/corr1810.html#abs-1810-03969
Ozsel Kilinc
Giovanni Montana
Multi-agent Deep Reinforcement Learning with Extremely Noisy Observations.
2018
abs/1812.00922
CoRR
http://arxiv.org/abs/1812.00922
db/journals/corr/corr1812.html#abs-1812-00922
Ricardo Pio Monti
Romy Lorenz
Peter Hellyer
Robert Leech
Christoforos Anagnostopoulos
Giovanni Montana
Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods.
2017
11
Frontiers Comput. Neurosci.
https://doi.org/10.3389/fncom.2017.00014
https://www.wikidata.org/entity/Q38857326
db/journals/ficn/ficn11.html#MontiLHLAM17
14
James H. Cole
Rudra P. K. Poudel
Dimosthenis Tsagkrasoulis
Matthan W. A. Caan
Claire J. Steves
Tim D. Spector
Giovanni Montana
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker.
115-124
2017
163
NeuroImage
https://doi.org/10.1016/j.neuroimage.2017.07.059
https://www.wikidata.org/entity/Q38648190
db/journals/neuroimage/neuroimage163.html#ColePTCSSM17
Zhana Kuncheva
Giovanni Montana
Multi-scale Community Detection in Temporal Networks Using Spectral Graph Wavelets.
139-154
2017
PAP@PKDD/ECML
https://doi.org/10.1007/978-3-319-71970-2_12
conf/pkdd/2017pap
db/conf/pkdd/pap2017.html#KunchevaM17
Zhana Kuncheva
Michelle L. Krishnan
Giovanni Montana
Exploring Brain Transcriptomic Patterns: A Topological Analysis Using Spatial Expression Networks.
70-81
2017
PSB
http://psb.stanford.edu/psb-online/proceedings/psb17/kuncheva.pdf
conf/psb/2017
db/conf/psb/psb2017.html#KunchevaKM17
Petros-Pavlos Ypsilantis
Giovanni Montana
Learning what to look in chest X-rays with a recurrent visual attention model.
2017
abs/1701.06452
CoRR
http://arxiv.org/abs/1701.06452
db/journals/corr/corr1701.html#YpsilantisM17
Zhana Kuncheva
Giovanni Montana
Multi-scale Community Detection in Temporal Networks Using Spectral Graph Wavelets.
2017
abs/1708.04060
CoRR
http://arxiv.org/abs/1708.04060
db/journals/corr/corr1708.html#abs-1708-04060
Emanuele Pesce
Petros-Pavlos Ypsilantis
Samuel Withey
Robert Bakewell
Vicky Goh
Giovanni Montana
Learning to detect chest radiographs containing lung nodules using visual attention networks.
2017
abs/1712.00996
CoRR
http://arxiv.org/abs/1712.00996
db/journals/corr/corr1712.html#abs-1712-00996
Mauro Annarumma
Giovanni Montana
Deep metric learning for multi-labelled radiographs.
2017
abs/1712.07682
CoRR
http://arxiv.org/abs/1712.07682
db/journals/corr/corr1712.html#abs-1712-07682
Michael W. Berry
Jung Jin Lee
Giovanni Montana
Stefan Van Aelst
Ruben H. Zamar
Special Issue on Advances in Data Mining and Robust Statistics.
388-389
2016
93
Comput. Stat. Data Anal.
https://doi.org/10.1016/j.csda.2015.09.004
db/journals/csda/csda93.html#BerryLMAZ16
Romy Lorenz
Ricardo Pio Monti
Inês R. Violante
Christoforos Anagnostopoulos
Aldo A. Faisal
Giovanni Montana
Robert Leech
The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI.
320-334
2016
129
NeuroImage
https://doi.org/10.1016/j.neuroimage.2016.01.032
https://www.wikidata.org/entity/Q27306682
db/journals/neuroimage/neuroimage129.html#LorenzMVAFML16
Ai Wern Chung
Markus Schirmer
Michelle L. Krishnan
Gareth Ball
Paul Aljabar
A. David Edwards
Giovanni Montana
Characterising brain network topologies: A dynamic analysis approach using heat kernels.
490-501
2016
141
NeuroImage
https://doi.org/10.1016/j.neuroimage.2016.07.006
https://www.wikidata.org/entity/Q39598090
db/journals/neuroimage/neuroimage141.html#ChungSKBAEM16
Savelie Cornegruta
Robert Bakewell
Samuel Withey
Giovanni Montana
Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks.
17-27
2016
Louhi@EMNLP
https://doi.org/10.18653/v1/W16-6103
conf/acl-louhi/2016
db/conf/acl-louhi/acl-louhi2016.html#CornegrutaBWM16
Rudra P. K. Poudel
Pablo Lamata
Giovanni Montana
Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation.
83-94
2016
RAMBO+HVSMR@MICCAI
https://doi.org/10.1007/978-3-319-52280-7_8
conf/miccai/2016rambo
db/conf/miccai/rambo2016.html#PoudelLM16
Ai Wern Chung
Emanuele Pesce
Ricardo Pio Monti
Giovanni Montana
Classifying HCP task-fMRI networks using heat kernels.
1-4
2016
PRNI
https://doi.org/10.1109/PRNI.2016.7552339
conf/prni/2016
db/conf/prni/prni2016.html#ChungPMM16
Romy Lorenz
Ricardo Pio Monti
Adam Hampshire
Yury Koush
Christoforos Anagnostopoulos
Aldo A. Faisal
David J. Sharp
Giovanni Montana
Robert Leech
Inês R. Violante
Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization.
1-4
2016
PRNI
https://doi.org/10.1109/PRNI.2016.7552338
https://www.wikidata.org/entity/Q57744831
conf/prni/2016
db/conf/prni/prni2016.html#LorenzMHKAFSMLV16
Ricardo Pio Monti
Romy Lorenz
Robert Leech
Christoforos Anagnostopoulos
Giovanni Montana
Text-mining the neurosynth corpus using deep boltzmann machines.
1-4
2016
PRNI
https://doi.org/10.1109/PRNI.2016.7552329
https://www.wikidata.org/entity/Q57744829
conf/prni/2016
db/conf/prni/prni2016.html#MontiLLAM16
Zi Wang
Vyacheslav Karolis
Chiara Nosarti
Giovanni Montana
Studying the brain from adolescence to adulthood through sparse multi-view matrix factorisations.
1-4
2016
PRNI
https://doi.org/10.1109/PRNI.2016.7552340
https://www.wikidata.org/entity/Q60499513
conf/prni/2016
db/conf/prni/prni2016.html#WangKNM16
Ricardo Pio Monti
Romy Lorenz
Robert Leech
Christoforos Anagnostopoulos
Giovanni Montana
Text-mining the NeuroSynth corpus using Deep Boltzmann Machines.
2016
abs/1605.00223
CoRR
http://arxiv.org/abs/1605.00223
db/journals/corr/corr1605.html#MontiLLAM16
Zi Wang
Vyacheslav Karolis
Chiara Nosarti
Giovanni Montana
Studying the brain from adolescence to adulthood through sparse multi-view matrix factorisations.
2016
abs/1605.02560
CoRR
http://arxiv.org/abs/1605.02560
db/journals/corr/corr1605.html#WangKNM16
Rudra P. K. Poudel
Pablo Lamata
Giovanni Montana
Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation.
2016
abs/1608.03974
CoRR
http://arxiv.org/abs/1608.03974
db/journals/corr/corr1608.html#PoudelLM16
Savelie Cornegruta
Robert Bakewell
Samuel Withey
Giovanni Montana
Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks.
2016
abs/1609.08409
CoRR
http://arxiv.org/abs/1609.08409
db/journals/corr/corr1609.html#CornegrutaBWM16
Petros-Pavlos Ypsilantis
Giovanni Montana
Recurrent Convolutional Networks for Pulmonary Nodule Detection in CT Imaging.
2016
abs/1609.09143
CoRR
http://arxiv.org/abs/1609.09143
db/journals/corr/corr1609.html#YpsilantisM16
Ricardo Pio Monti
Christoforos Anagnostopoulos
Giovanni Montana
A framework for adaptive regularization in streaming Lasso models.
2016
abs/1610.09127
CoRR
http://arxiv.org/abs/1610.09127
db/journals/corr/corr1610.html#MontiAM16
James H. Cole
Rudra P. K. Poudel
Dimosthenis Tsagkrasoulis
Matthan W. A. Caan
Claire J. Steves
Tim D. Spector
Giovanni Montana
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker.
2016
abs/1612.02572
CoRR
http://arxiv.org/abs/1612.02572
db/journals/corr/corr1612.html#ColePTCSSM16
Zi Wang
Wei Yuan
Giovanni Montana
Sparse multi-view matrix factorization: a multivariate approach to multiple tissue comparisons.
3163-3171
2015
31
Bioinform.
19
https://doi.org/10.1093/bioinformatics/btv344
https://www.wikidata.org/entity/Q35655137
db/journals/bioinformatics/bioinformatics31.html#WangYM15
Da Ruan 0002
Alastair Young
Giovanni Montana
Differential analysis of biological networks.
327:1-327:13
2015
16
BMC Bioinform.
https://doi.org/10.1186/s12859-015-0735-5
https://www.wikidata.org/entity/Q35802316
db/journals/bmcbi/bmcbi16.html#RuanYM15
Zhana Kuncheva
Giovanni Montana
Community Detection in Multiplex Networks using Locally Adaptive Random Walks.
1308-1315
2015
ASONAM
https://doi.org/10.1145/2808797.2808852
conf/asunam/2015
db/conf/asunam/asonam2015.html#KunchevaM15
Alexandre de Brébisson
Giovanni Montana
Deep neural networks for anatomical brain segmentation.
20-28
2015
CVPR Workshops
https://doi.org/10.1109/CVPRW.2015.7301312
https://doi.ieeecomputersociety.org/10.1109/CVPRW.2015.7301312
conf/cvpr/2015w
db/conf/cvpr/cvprw2015.html#BrebissonM15
Eva Janousová
Daniel Schwarz
Giovanni Montana
Tomás Kaspárek
Brain image classification based on automated morphometry and penalised linear discriminant analysis with resampling.
263-268
2015
FedCSIS
https://doi.org/10.15439/2015F147
https://www.wikidata.org/entity/Q60620424
conf/fedcsis/2015
db/conf/fedcsis/fedcsis2015.html#JanousovaSMK15
Adrien Payan
Giovanni Montana
Predicting Alzheimer's Disease - A Neuroimaging Study with 3D Convolutional Neural Networks.
355-362
2015
ICPRAM (2)
conf/icpram/2015-2
db/conf/icpram/icpram2015-2.html#PayanM15
Ricardo Pio Monti
Romy Lorenz
Peter Hellyer
Robert Leech
Christoforos Anagnostopoulos
Giovanni Montana
Graph Embeddings of Dynamic Functional Connectivity Reveal Discriminative Patterns of Task Engagement in HCP Data.
1-4
2015
PRNI
https://doi.org/10.1109/PRNI.2015.21
https://doi.ieeecomputersociety.org/10.1109/PRNI.2015.21
https://www.wikidata.org/entity/Q57744837
conf/prni/2015
db/conf/prni/prni2015.html#MontiLHLAM15
Alexandre de Brébisson
Giovanni Montana
Deep Neural Networks for Anatomical Brain Segmentation.
2015
abs/1502.02445
CoRR
http://arxiv.org/abs/1502.02445
db/journals/corr/corr1502.html#BrebissonM15
Adrien Payan
Giovanni Montana
Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks.
2015
abs/1502.02506
CoRR
http://arxiv.org/abs/1502.02506
db/journals/corr/corr1502.html#PayanM15
Zhana Kuncheva
Giovanni Montana
Community detection in multiplex networks using locally adaptive random walks.
2015
abs/1507.01890
CoRR
http://arxiv.org/abs/1507.01890
db/journals/corr/corr1507.html#KunchevaM15
Zi Wang
Edward W. J. Curry
Giovanni Montana
Network-guided regression for detecting associations between DNA methylation and gene expression.
2693-2701
2014
30
Bioinform.
19
https://doi.org/10.1093/bioinformatics/btu361
https://www.wikidata.org/entity/Q46132991
db/journals/bioinformatics/bioinformatics30.html#WangCM14
Alberto Cozzini
Ajay Jasra
Giovanni Montana
Adam Persing
A Bayesian mixture of lasso regressions with t-errors.
84-97
2014
77
Comput. Stat. Data Anal.
https://doi.org/10.1016/j.csda.2014.03.018
db/journals/csda/csda77.html#CozziniJMP14
Brian McWilliams
Giovanni Montana
Subspace clustering of high-dimensional data: a predictive approach.
736-772
2014
28
Data Min. Knowl. Discov.
3
https://doi.org/10.1007/s10618-013-0317-y
db/journals/datamine/datamine28.html#McWilliamsM14
Ricardo Pio Monti
Peter Hellyer
David J. Sharp
Robert Leech
Christoforos Anagnostopoulos
Giovanni Montana
Estimating time-varying brain connectivity networks from functional MRI time series.
427-443
2014
103
NeuroImage
https://doi.org/10.1016/j.neuroimage.2014.07.033
https://www.wikidata.org/entity/Q45798515
db/journals/neuroimage/neuroimage103.html#MontiHSLAM14
Christopher Minas
Giovanni Montana
Distance-Based Analysis of Variance: Approximate Inference.
450-470
2014
7
Stat. Anal. Data Min.
6
https://doi.org/10.1002/sam.11227
db/journals/sadm/sadm7.html#MinasM14
Christopher Minas
Edward W. J. Curry
Giovanni Montana
A distance-based test of association between paired heterogeneous genomic data.
2555-2563
2013
29
Bioinform.
20
https://doi.org/10.1093/bioinformatics/btt450
https://www.wikidata.org/entity/Q30659492
db/journals/bioinformatics/bioinformatics29.html#MinasCM13
Yue Wang 0006
Wilson Wen Bin Goh
Limsoon Wong
Giovanni Montana
Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.
S6
2013
14
BMC Bioinform.
S-16
https://doi.org/10.1186/1471-2105-14-S16-S6
https://www.wikidata.org/entity/Q35101681
db/journals/bmcbi/bmcbi14S.html#0006GWM13
Alberto Cozzini
Ajay Jasra
Giovanni Montana
Model-Based Clustering with gene Ranking using penalized Mixtures of heavy-tailed Distributions.
2013
11
J. Bioinform. Comput. Biol.
3
https://doi.org/10.1142/S0219720013410072
https://www.wikidata.org/entity/Q43688816
db/journals/jbcb/jbcb11.html#CozziniJM13
Maria Vounou
Eva Janousová
Robin Wolz
Jason L. Stein
Paul M. Thompson
Daniel Rueckert
Giovanni Montana
Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease.
700-716
2012
60
NeuroImage
1
https://doi.org/10.1016/j.neuroimage.2011.12.029
https://www.wikidata.org/entity/Q36551568
db/journals/neuroimage/neuroimage60.html#VounouJWSTRM12
Matt Silver
Eva Janousová
Xue Hua
Paul M. Thompson
Giovanni Montana
Identification of gene pathways implicated in Alzheimer's disease using longitudinal imaging phenotypes with sparse regression.
1681-1694
2012
63
NeuroImage
3
https://doi.org/10.1016/j.neuroimage.2012.08.002
https://www.wikidata.org/entity/Q36546976
db/journals/neuroimage/neuroimage63.html#SilverJHTM12
Brian McWilliams
Giovanni Montana
Multi-view predictive partitioning in high dimensions.
304-321
2012
5
Stat. Anal. Data Min.
4
https://doi.org/10.1002/sam.11144
db/journals/sadm/sadm5.html#McWilliamsM12
Maurice Berk
Giovanni Montana
A Skew-t-Normal Multi-level Reduced-Rank Functional PCA Model for the Analysis of Replicated Genomics Time Course Data.
56-66
2012
IDA
https://doi.org/10.1007/978-3-642-34156-4_7
conf/ida/2012
db/conf/ida/ida2012.html#BerkM12
Maurice Berk
Timothy M. D. Ebbels
Giovanni Montana
A statistical framework for biomarker discovery in metabolomic time course data.
1979-1985
2011
27
Bioinform.
14
https://doi.org/10.1093/bioinformatics/btr289
https://www.wikidata.org/entity/Q33951348
db/journals/bioinformatics/bioinformatics27.html#BerkEM11
Christopher Minas
Simon J. Waddell
Giovanni Montana
Distance-based differential analysis of gene curves.
3135-3141
2011
27
Bioinform.
22
https://doi.org/10.1093/bioinformatics/btr528
https://www.wikidata.org/entity/Q48106224
db/journals/bioinformatics/bioinformatics27.html#MinasWM11
Kostas Triantafyllopoulos
Giovanni Montana
Dynamic modeling of mean-reverting spreads for statistical arbitrage.
23-49
2011
8
Comput. Manag. Sci.
1-2
https://doi.org/10.1007/s10287-009-0105-8
db/journals/cms/cms8.html#Triantafyllopoulos11
Matt Silver
Giovanni Montana
Thomas E. Nichols
False positives in neuroimaging genetics using voxel-based morphometry data.
992-1000
2011
54
NeuroImage
2
https://doi.org/10.1016/j.neuroimage.2010.08.049
https://www.wikidata.org/entity/Q33695094
db/journals/neuroimage/neuroimage54.html#SilverMN11
Brian McWilliams
Giovanni Montana
Predictive Subspace Clustering.
247-252
2011
ICMLA (1)
https://doi.org/10.1109/ICMLA.2011.117
https://doi.ieeecomputersociety.org/10.1109/ICMLA.2011.117
conf/icmla/2011-1
db/conf/icmla/icmla2011-1.html#McWilliamsM11
Eva Janousová
Maria Vounou
Robin Wolz
Katherine R. Gray
Daniel Rueckert
Giovanni Montana
Fast Brain-Wide Search of Highly Discriminative Regions in Medical Images: an Application to Alzheimers Disease.
17-22
2011
MIUA
conf/miua/2011
db/conf/miua/miua2011.html#JanousovaVWGRM11
Maria Vounou
Thomas E. Nichols
Giovanni Montana
Discovering genetic associations with high-dimensional neuroimaging phenotypes: A sparse reduced-rank regression approach.
1147-1159
2010
53
NeuroImage
3
https://doi.org/10.1016/j.neuroimage.2010.07.002
https://www.wikidata.org/entity/Q37597727
db/journals/neuroimage/neuroimage53.html#VounouNM10
Brian McWilliams
Giovanni Montana
Sparse partial least squares regression for on-line variable selection with multivariate data streams.
170-193
2010
3
Stat. Anal. Data Min.
3
https://doi.org/10.1002/sam.10074
db/journals/sadm/sadm3.html#McWilliamsM10
Giovanni Montana
Kostas Triantafyllopoulos
Theodoros Tsagaris
Flexible least squares for temporal data mining and statistical arbitrage.
2819-2830
2009
36
Expert Syst. Appl.
2
https://doi.org/10.1016/j.eswa.2008.01.062
db/journals/eswa/eswa36.html#MontanaTT09
Giovanni Montana
Francesco Parrella
Learning to Trade with Incremental Support Vector Regression Experts.
591-598
2008
HAIS
https://doi.org/10.1007/978-3-540-87656-4_73
conf/hais/2008
db/conf/hais/hais2008.html#MontanaP08
Giovanni Montana
Kostas Triantafyllopoulos
Theodoros Tsagaris
Data stream mining for market-neutral algorithmic trading.
966-970
2008
SAC
https://doi.org/10.1145/1363686.1363910
conf/sac/2008
db/conf/sac/sac2008.html#MontanaTT08
Giovanni Montana
Clive J. Hoggart
Statistical software for gene mapping by admixture linkage disequilibrium.
393-395
2007
8
Briefings Bioinform.
6
https://doi.org/10.1093/bib/bbm035
https://www.wikidata.org/entity/Q36886637
db/journals/bib/bib8.html#MontanaH07
Giovanni Montana
Statistical methods in genetics.
297-308
2006
7
Briefings Bioinform.
3
https://doi.org/10.1093/bib/bbl028
https://www.wikidata.org/entity/Q36590301
db/journals/bib/bib7.html#Montana06
Giovanni Montana
HapSim: a simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients.
4309-4311
2005
21
Bioinform.
23
https://doi.org/10.1093/bioinformatics/bti689
https://www.wikidata.org/entity/Q31007547
db/journals/bioinformatics/bioinformatics21.html#Montana05
Stefan Van Aelst
Paul Aljabar
Ashik Amlani
Christoforos Anagnostopoulos
Mauro Annarumma
Emma C. Atakpa
Robert Bakewell
Gareth Ball
Gareth J. Barker
Alex Beeson
Maurice Berk
Michael W. Berry
Jürgen Branke
Alexandre de Brébisson
Adam R. Brentnall
Nicholas ByrneNick Byrne
Matthan W. A. Caan
Henry Charlesworth
Ai Wern Chung
James R. Clough
James H. Cole
Savelie Cornegruta
Erich Cosmi
Alberto Cozzini
Edward W. J. Curry
Jack Cuzick
Celeste Damiani
Pallab Dasgupta
Sumanta Dey
Stephen W. Duffy
Timothy M. D. Ebbels
A. David Edwards
A. Aldo FaisalAldo A. Faisal
Briti Gangopadhyay
Mingqi Gao 0003
Aydan Gasimova
Vicky Goh
Wilson Wen Bin Goh
Katherine R. Gray
Enrico Grisan
Adam Hampshire
Jungong Han
Peter Hellyer
Charles A. Hepburn
Harry Hill
Clive J. Hoggart
Yang Hu
Xue Hua
Charles Hutchinson
David Ireland
Eva Janousová
Ajay Jasra
Paul A. Jennings
Yue Jin
Vyacheslav Karolis
Tomás Kaspárek
Siddartha Khastgir
Ozsel Kilinc
Andrew P. King
Yury Koush
Michelle L. Krishnan
Zhana Kuncheva
Pablo Lamata
Jung Jin Lee
Robert Leech
Romy Lorenz
Ke Lu
Matthew MacPherson
Brian McWilliams
Christopher Minas
Saad Mohamad
Ricardo Pio Monti
Keerthini Muthuswamy
Thomas E. Nichols
Chiara Nosarti
Francesco Parrella
Adrien Payan
Adam Persing
Emanuele Pesce
Rudra P. K. Poudel
Da Ruan 0002
Daniel Rueckert
Ruggiero Santeramo
Nicoló Savioli
Markus Schirmer
Daniel Schwarz
David J. Sharp
Matt Silver
Ksenia Sokolova
Tim D. Spector
Jason L. Stein
Claire J. Steves
Paul M. Thompson
Kostas Triantafyllopoulos
Theodoros Tsagaris
Dimosthenis Tsagkrasoulis
Isra Valverde
Israel Valverde
Miguel S. VieiraMiguel Silva Vieira
Inês R. Violante
Silvia Visentin
Maria Vounou
Simon J. Waddell
Mianchu Wang
Yue Wang 0006
Zi Wang
George Watkins
Samuel Withey
Robin Wolz
Limsoon Wong
Jinyu Yang
Alastair Young
Petros-Pavlos Ypsilantis
James Jian Qiao YuJames J. Q. Yu
Wei Yuan
Ruben H. Zamar
Feng Zheng