Pavel Izmailov
Pavel Izmailov
PhD Student, NYU
Verified email at nyu.edu - Homepage
Title
Cited by
Cited by
Year
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
1632018
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
1062018
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
642019
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
63*2018
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition
P Izmailov, A Novikov, D Kropotov
Artificial Intelligence and Statistics (AISTATS), 2018
152018
Subspace Inference for Bayesian Deep Learning
P Izmailov, WJ Maddox, P Kirichenko, T Garipov, D Vetrov, AG Wilson
Uncertainty in Artificial Intelligence (UAI), 2019
102019
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
AG Wilson, P Izmailov
arXiv preprint arXiv:2002.08791, 2020
92020
Tensor Train decomposition on TensorFlow (T3F)
A Novikov, P Izmailov, V Khrulkov, M Figurnov, I Oseledets
Journal of Machine Learning Research 21, 2020
82020
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
82018
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
52020
Semi-Supervised Learning with Normalizing Flows
P Izmailov, P Kirichenko, M Finzi, AG Wilson
International Conference on Machine Learning (ICML), 2019
52019
Invertible Convolutional Networks
M Finzi, P Izmailov, W Maddox, P Kirichenko, AG Wilson
Workshop on Invertible Neural Nets and Normalizing Flows at ICML, 2019
42019
Fast Uncertainty Estimates and Bayesian Model Averaging of DNNs
W Maddox, T Garipov, P Izmailov, D Vetrov, AG Wilson
Uncertainty in Deep Learning Workshop at UAI, 2018
12018
Faster variational inducing input Gaussian process classification
P Izmailov, D Kropotov
Machine Learning and Data Analysis 4 (3), 20-35, 2017
12017
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
P Kirichenko, P Izmailov, AG Wilson
arXiv preprint arXiv:2006.08545, 2020
2020
Алгоритмы обучения гауссовских процессов для больших объемов данных
ПА Измаилов
ББК 22 С23, 64, 2017
2017
Gaussian Processes for Machine Learning
P Izmailov
2016
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Articles 1–17