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Pavel Izmailov
Pavel Izmailov
Anthropic; NYU
Bestätigte E-Mail-Adresse bei openai.com - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Averaging Weights Leads to Wider Optima and Better Generalization
P Izmailov, D Podoprikhin, T Garipov, D Vetrov, AG Wilson
Uncertainty in Artificial Intelligence (UAI), 2018
15132018
A Simple Baseline for Bayesian Uncertainty in Deep Learning
W Maddox, T Garipov, P Izmailov, D Vetrov, AG Wilson
Advances in Neural Information Processing Systems (NeurIPS), 2019
8172019
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
T Garipov, P Izmailov, D Podoprikhin, DP Vetrov, AG Wilson
Advances in Neural Information Processing Systems (NeurIPS), 2018
6552018
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
AG Wilson, P Izmailov
Advances in Neural Information Processing Systems (NeurIPS), 2020
6262020
What Are Bayesian Neural Network Posteriors Really Like?
P Izmailov, S Vikram, MD Hoffman, AG Wilson
International Conference on Machine Learning (ICML), 2021
3332021
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data
M Finzi, S Stanton, P Izmailov, AG Wilson
International Conference on Machine Learning (ICML), 2020
2912020
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
B Athiwaratkun, M Finzi, P Izmailov, AG Wilson
International Conference on Learning Representations (ICLR 2019), 2018
289*2018
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
P Kirichenko, P Izmailov, AG Wilson
Advances in Neural Information Processing Systems (NeurIPS), 2020
2332020
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
P Kirichenko, P Izmailov, AG Wilson
International Conference on Learning Representations (ICLR 2023), 2022
2062022
Does Knowledge Distillation Really Work?
S Stanton, P Izmailov, P Kirichenko, AA Alemi, AG Wilson
Advances in Neural Information Processing Systems (NeurIPS), 2021
1762021
Subspace Inference for Bayesian Deep Learning
P Izmailov, WJ Maddox, P Kirichenko, T Garipov, D Vetrov, AG Wilson
Uncertainty in Artificial Intelligence (UAI), 2019
1642019
Learning Invariances in Neural Networks
G Benton, M Finzi, P Izmailov, AG Wilson
Advances in Neural Information Processing Systems (NeurIPS), 2020
138*2020
Semi-Supervised Learning with Normalizing Flows
P Izmailov, P Kirichenko, M Finzi, AG Wilson
International Conference on Machine Learning (ICML), 2019
1222019
On Feature Learning in the Presence of Spurious Correlations
P Izmailov, P Kirichenko, N Gruver, AG Wilson
Advances in Neural Information Processing Systems (NeurIPS), 2022
732022
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition
P Izmailov, A Novikov, D Kropotov
Artificial Intelligence and Statistics (AISTATS), 2018
652018
Tensor Train decomposition on TensorFlow (T3F)
A Novikov, P Izmailov, V Khrulkov, M Figurnov, I Oseledets
Journal of Machine Learning Research 21, 2020
632020
FlexiViT: One Model for All Patch Sizes
L Beyer, P Izmailov, A Kolesnikov, M Caron, S Kornblith, X Zhai, ...
Conference on Computer Vision and Pattern Recognition (CVPR 2023), 2022
572022
Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision
C Burns, P Izmailov, JH Kirchner, B Baker, L Gao, L Aschenbrenner, ...
532023
Bayesian Model Selection, the Marginal Likelihood, and Generalization
S Lotfi, P Izmailov, G Benton, M Goldblum, AG Wilson
International Conference on Machine Learning (ICML), 2022
522022
Improving Stability in Deep Reinforcement Learning with Weight Averaging
E Nikishin, P Izmailov, B Athiwaratkun, D Podoprikhin, T Garipov, ...
Uncertainty in Deep Learning Workshop at UAI, 2018
452018
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