Pavel Izmailov

53 papers A* 17A 3Journal 30Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	From Entropy to Epiplexity: Rethinking Information for Computationally Bounded Intelligence. CoRR Marc Finzi, Shikai Qiu, Yiding Jiang, Pavel Izmailov, J. Zico Kolter, Andrew Gordon Wilson
2026	J	`jnl`	Reliable and Responsible Foundation Models: A Comprehensive Survey. CoRR Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2025	J	`jnl`	Closing the Train-Test Gap in World Models for Gradient-Based Planning. CoRR Arjun Parthasarathy, Nimit Kalra, Rohun Agrawal, Yann LeCun, Oumayma Bounou, Pavel Izmailov, Micah Goldblum
2025	J	`jnl`	Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes. CoRR Joseph Hoche, Andrei Bursuc, David Brellmann, Gilles Louppe, Pavel Izmailov, Angela Yao, Gianni Franchi
2025	J	`jnl`	Reliable and Responsible Foundation Models. Trans. Mach. Learn. Res. Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Gordon Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2024	J	`jnl`	Can a Confident Prior Replace a Cold Posterior? CoRR Martin Marek, Brooks Paige, Pavel Izmailov
2024	A*	`conf`	Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision. ICML Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, Bowen Baker, Leo Gao, Leopold Aschenbrenner, Yining Chen, Adrien Ecoffet, Manas Joglekar, Jan Leike, Ilya Sutskever, Jeffrey Wu
2023	—	`—`	Deconstructing Models and Methods in Deep Learning Pavel Izmailov
2023	A*	`conf`	FlexiViT: One Model for All Patch Sizes. CVPR Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
2023	A*	`conf`	Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations. ICLR Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson
2023	A*	`conf`	Simple and Fast Group Robustness by Automatic Feature Reweighting. ICML Shikai Qiu, Andres Potapczynski, Pavel Izmailov, Andrew Gordon Wilson
2023	J	`jnl`	Simple and Fast Group Robustness by Automatic Feature Reweighting. CoRR Shikai Qiu, Andres Potapczynski, Pavel Izmailov, Andrew Gordon Wilson
2023	J	`jnl`	Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision. CoRR Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, Bowen Baker, Leo Gao, Leopold Aschenbrenner, Yining Chen, Adrien Ecoffet, Manas Joglekar, Jan Leike, Ilya Sutskever, Jeff Wu
2022	A*	`conf`	Bayesian Model Selection, the Marginal Likelihood, and Generalization. ICML Sanae Lotfi, Pavel Izmailov, Gregory W. Benton, Micah Goldblum, Andrew Gordon Wilson
2022	J	`jnl`	Bayesian Model Selection, the Marginal Likelihood, and Generalization. CoRR Sanae Lotfi, Pavel Izmailov, Gregory W. Benton, Micah Goldblum, Andrew Gordon Wilson
2022	J	`jnl`	FlexiViT: One Model for All Patch Sizes. CoRR Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
2022	J	`jnl`	Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations. CoRR Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson
2022	A*	`conf`	On Feature Learning in the Presence of Spurious Correlations. NeurIPS Pavel Izmailov, Polina Kirichenko, Nate Gruver, Andrew Gordon Wilson
2022	J	`jnl`	On Feature Learning in the Presence of Spurious Correlations. CoRR Pavel Izmailov, Polina Kirichenko, Nate Gruver, Andrew Gordon Wilson
2022	A*	`conf`	On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification. NeurIPS Sanyam Kapoor, Wesley J. Maddox, Pavel Izmailov, Andrew Gordon Wilson
2022	J	`jnl`	On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification. CoRR Sanyam Kapoor, Wesley J. Maddox, Pavel Izmailov, Andrew Gordon Wilson
2021	A*	`conf`	Dangers of Bayesian Model Averaging under Covariate Shift. NeurIPS Pavel Izmailov, Patrick Nicholson, Sanae Lotfi, Andrew Gordon Wilson
2021	J	`jnl`	Dangers of Bayesian Model Averaging under Covariate Shift. CoRR Pavel Izmailov, Patrick Nicholson, Sanae Lotfi, Andrew Gordon Wilson
2021	A*	`conf`	Does Knowledge Distillation Really Work? NeurIPS Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson
2021	J	`jnl`	Does Knowledge Distillation Really Work? CoRR Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson
2021	—	`conf`	Evaluating Approximate Inference in Bayesian Deep Learning. NeurIPS (Competition and Demos) Andrew Gordon Wilson, Pavel Izmailov, Matthew D. Hoffman, Yarin Gal, Yingzhen Li, Melanie F. Pradier, Sharad Vikram, Andrew Y. K. Foong, Sanae Lotfi, Sebastian Farquhar
2021	A*	`conf`	What Are Bayesian Neural Network Posteriors Really Like? ICML Pavel Izmailov, Sharad Vikram, Matthew D. Hoffman, Andrew Gordon Wilson
2021	J	`jnl`	What Are Bayesian Neural Network Posteriors Really Like? CoRR Pavel Izmailov, Sharad Vikram, Matthew D. Hoffman, Andrew Gordon Wilson
2020	A*	`conf`	Bayesian Deep Learning and a Probabilistic Perspective of Generalization. NeurIPS Andrew Gordon Wilson, Pavel Izmailov
2020	J	`jnl`	Bayesian Deep Learning and a Probabilistic Perspective of Generalization. CoRR Andrew Gordon Wilson, Pavel Izmailov
2020	A*	`conf`	Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. ICML Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson
2020	J	`jnl`	Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. CoRR Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson
2020	A*	`conf`	Learning Invariances in Neural Networks from Training Data. NeurIPS Gregory W. Benton, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson
2020	J	`jnl`	Learning Invariances in Neural Networks. CoRR Gregory W. Benton, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson
2020	A*	`conf`	Semi-Supervised Learning with Normalizing Flows. ICML Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Gordon Wilson
2020	J	`jnl`	Tensor Train Decomposition on TensorFlow (T3F). J. Mach. Learn. Res. Alexander Novikov, Pavel Izmailov, Valentin Khrulkov, Michael Figurnov, Ivan V. Oseledets
2020	A*	`conf`	Why Normalizing Flows Fail to Detect Out-of-Distribution Data. NeurIPS Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson
2020	J	`jnl`	Why Normalizing Flows Fail to Detect Out-of-Distribution Data. CoRR Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson
2019	A*	`conf`	A Simple Baseline for Bayesian Uncertainty in Deep Learning. NeurIPS Wesley J. Maddox, Pavel Izmailov, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson
2019	J	`jnl`	A Simple Baseline for Bayesian Uncertainty in Deep Learning. CoRR Wesley J. Maddox, Timur Garipov, Pavel Izmailov, Dmitry P. Vetrov, Andrew Gordon Wilson
2019	J	`jnl`	Semi-Supervised Learning with Normalizing Flows. CoRR Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Gordon Wilson
2019	A	`conf`	Subspace Inference for Bayesian Deep Learning. UAI Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson
2019	J	`jnl`	Subspace Inference for Bayesian Deep Learning. CoRR Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson
2019	—	`conf`	There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average. ICLR (Poster) Ben Athiwaratkun, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson
2018	A	`conf`	Averaging Weights Leads to Wider Optima and Better Generalization. UAI Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson
2018	J	`jnl`	Averaging Weights Leads to Wider Optima and Better Generalization. CoRR Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson
2018	J	`jnl`	Improving Consistency-Based Semi-Supervised Learning with Weight Averaging. CoRR Ben Athiwaratkun, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson
2018	A*	`conf`	Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs. NeurIPS Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P. Vetrov, Andrew Gordon Wilson
2018	J	`jnl`	Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs. CoRR Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P. Vetrov, Andrew Gordon Wilson
2018	A	`conf`	Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition. AISTATS Pavel Izmailov, Alexander Novikov, Dmitry Kropotov
2018	J	`jnl`	Tensor Train decomposition on TensorFlow (T3F). CoRR Alexander Novikov, Pavel Izmailov, Valentin Khrulkov, Michael Figurnov, Ivan V. Oseledets
2017	J	`jnl`	Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition. CoRR Pavel Izmailov, Alexander Novikov, Dmitry Kropotov
2016	J	`jnl`	Faster variational inducing input Gaussian process classification. CoRR Pavel Izmailov, Dmitry Kropotov