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Author search results
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- Padhraic Smyth
University of California, Irvine, Department of Computer Science, CA, USA
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Publication search results
found 236 matches
- 2024
- Mark Steyvers, Heliodoro Tejeda Lemus, Aakriti Kumar, Catarina Belém, Sheer Karny, Xinyue Hu, Lukas Mayer, Padhraic Smyth:
The Calibration Gap between Model and Human Confidence in Large Language Models. CoRR abs/2401.13835 (2024) - 2023
- Edgar E. Robles, Ye Jin, Padhraic Smyth, Richard H. Scheuermann, Jack D. Bui, Huan-You Wang, Jean Oak, Yu Qian:
A cell-level discriminative neural network model for diagnosis of blood cancers. Bioinform. 39(10) (2023) - Markelle Kelly, Padhraic Smyth:
Variable-Based Calibration for Machine Learning Classifiers. AAAI 2023: 8211-8219 - Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth:
Probabilistic Querying of Continuous-Time Event Sequences. AISTATS 2023: 10235-10251 - Gavin Kerrigan, Justin Ley, Padhraic Smyth:
Diffusion Generative Models in Infinite Dimensions. AISTATS 2023: 9538-9563 - Markelle Kelly, Aakriti Kumar, Padhraic Smyth, Mark Steyvers:
Capturing Humans' Mental Models of AI: An Item Response Theory Approach. FAccT 2023: 1723-1734 - Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph:
Deep Anomaly Detection under Labeling Budget Constraints. ICML 2023: 19882-19910 - Hyungrok Do, Yuxin Chang, Yoon-Sang Cho, Padhraic Smyth, Judy Zhong:
When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations. MLHC 2023: 128-149 - Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt:
Zero-Shot Anomaly Detection via Batch Normalization. NeurIPS 2023 - Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth:
Inference for mark-censored temporal point processes. UAI 2023: 226-236 - Aodong Li, Chen Qiu, Padhraic Smyth, Marius Kloft, Stephan Mandt, Maja Rudolph:
Deep Anomaly Detection under Labeling Budget Constraints. CoRR abs/2302.07832 (2023) - Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt:
Zero-Shot Anomaly Detection without Foundation Models. CoRR abs/2302.07849 (2023) - Markelle Kelly, Aakriti Kumar, Padhraic Smyth, Mark Steyvers:
Capturing Humans' Mental Models of AI: An Item Response Theory Approach. CoRR abs/2305.09064 (2023) - Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth:
Functional Flow Matching. CoRR abs/2305.17209 (2023) - Samuel Showalter, Alex Boyd, Padhraic Smyth, Mark Steyvers:
Bayesian Online Learning for Consensus Prediction. CoRR abs/2312.07679 (2023) - Yuxin Chang, Alex Boyd, Padhraic Smyth:
Probabilistic Modeling for Sequences of Sets in Continuous-Time. CoRR abs/2312.15045 (2023) - 2022
- Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams:
Automating data science. Commun. ACM 65(3): 76-87 (2022) - Hyungrok Do, Preston Putzel, Axel S. Martin, Padhraic Smyth, Judy Zhong:
Fair Generalized Linear Models with a Convex Penalty. ICML 2022: 5286-5308 - Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth:
Predictive Querying for Autoregressive Neural Sequence Models. NeurIPS 2022 - Hyungrok Do, Preston Putzel, Axel S. Martin, Padhraic Smyth, Judy Zhong:
Fair Generalized Linear Models with a Convex Penalty. CoRR abs/2206.09076 (2022) - Markelle Kelly, Padhraic Smyth:
Variable-Based Calibration for Machine Learning Classifiers. CoRR abs/2209.15154 (2022) - Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth:
Predictive Querying for Autoregressive Neural Sequence Models. CoRR abs/2210.06464 (2022) - Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth:
Probabilistic Querying of Continuous-Time Event Sequences. CoRR abs/2211.08499 (2022) - Gavin Kerrigan, Justin Ley, Padhraic Smyth:
Diffusion Generative Models in Infinite Dimensions. CoRR abs/2212.00886 (2022) - 2021
- Disi Ji, Robert L. Logan IV, Padhraic Smyth, Mark Steyvers:
Active Bayesian Assessment of Black-Box Classifiers. AAAI 2021: 7935-7944 - Preston Putzel, Hyungrok Do, Alex Boyd, Hua Zhong, Padhraic Smyth:
Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions. MLHC 2021: 648-673 - Gavin Kerrigan, Padhraic Smyth, Mark Steyvers:
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration. NeurIPS 2021: 4421-4434 - Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt:
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning. NeurIPS 2021: 6816-6828 - Preston Putzel, Padhraic Smyth, Jaehong Yu, Hua Zhong:
Dynamic Survival Analysis with Individualized Truncated Parametric Distributions. SPACA 2021: 159-170 - Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams:
Automating Data Science: Prospects and Challenges. CoRR abs/2105.05699 (2021)
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