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2020 – today
- 2022
[c10]Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, Victor Lempitsky:
Resolution-robust Large Mask Inpainting with Fourier Convolutions. WACV 2022: 3172-3182- 2021
- [i10]Arsenii Ashukha, Andrei Atanov, Dmitry P. Vetrov:
Mean Embeddings with Test-Time Data Augmentation for Ensembling of Representations. CoRR abs/2106.08038 (2021) - [i9]Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, Victor Lempitsky:
Resolution-robust Large Mask Inpainting with Fourier Convolutions. CoRR abs/2109.07161 (2021) - [i8]Arsenii Kuznetsov, Alexander Grishin, Artem Tsypin, Arsenii Ashukha, Dmitry P. Vetrov:
Automating Control of Overestimation Bias for Continuous Reinforcement Learning. CoRR abs/2110.13523 (2021) - 2020
- [c9]Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov:
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. ICLR 2020 - [c8]Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha
, Dmitry Molchanov, Dmitry P. Vetrov:
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. UAI 2020: 1308-1317 - [i7]Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov:
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. CoRR abs/2002.06470 (2020) - [i6]Dmitry Molchanov, Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry P. Vetrov:
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. CoRR abs/2002.09103 (2020)
2010 – 2019
- 2019
- [c7]Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling:
The Deep Weight Prior. ICLR (Poster) 2019 - [c6]Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Variance Networks: When Expectation Does Not Meet Your Expectations. ICLR (Poster) 2019 - [c5]Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov:
Uncertainty Estimation via Stochastic Batch Normalization. ISNN (1) 2019: 261-269 - [i5]Andrei Atanov, Alexandra Volokhova, Arsenii Ashukha, Ivan Sosnovik, Dmitry P. Vetrov:
Semi-Conditional Normalizing Flows for Semi-Supervised Learning. CoRR abs/1905.00505 (2019) - 2018
- [c4]Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov:
Uncertainty Estimation via Stochastic Batch Normalization. ICLR (Workshop) 2018 - [c3]Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Bayesian Incremental Learning for Deep Neural Networks. ICLR (Workshop) 2018 - [i4]Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov:
Uncertainty Estimation via Stochastic Batch Normalization. CoRR abs/1802.04893 (2018) - [i3]Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Bayesian Incremental Learning for Deep Neural Networks. CoRR abs/1802.07329 (2018) - [i2]Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling:
The Deep Weight Prior. Modeling a prior distribution for CNNs using generative models. CoRR abs/1810.06943 (2018) - 2017
- [c2]Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Variational Dropout Sparsifies Deep Neural Networks. ICML 2017: 2498-2507 - [c1]Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Structured Bayesian Pruning via Log-Normal Multiplicative Noise. NIPS 2017: 6775-6784 - [i1]Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Variational Dropout Sparsifies Deep Neural Networks. CoRR abs/1701.05369 (2017)
Coauthor Index
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