Arsenii Ashukha

Publication Activity (10 Years)

Years Active: 2017-2022
Publications (10 Years): 20

Top Topics

Reinforcement Learning

Stochastic Simulation

Top Venues

ICLR (Workshop)

Publications

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)
Arsenii Ashukha, Andrei Atanov, Dmitry P. Vetrov
Mean Embeddings with Test-Time Data Augmentation for Ensembling of Representations. CoRR (2021)
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 (2021)
Arsenii Kuznetsov, Alexander Grishin, Artem Tsypin, Arsenii Ashukha, Dmitry P. Vetrov
Automating Control of Overestimation Bias for Continuous Reinforcement Learning. CoRR (2021)
Dmitry Molchanov, Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry P. Vetrov
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. CoRR (2020)
Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. CoRR (2020)
Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. ICLR (2020)
Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry Molchanov, Dmitry P. Vetrov
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. UAI (2020)
Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling
The Deep Weight Prior. ICLR (Poster) (2019)
Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
Uncertainty Estimation via Stochastic Batch Normalization. ISNN (1) (2019)
Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Variance Networks: When Expectation Does Not Meet Your Expectations. ICLR (Poster) (2019)
Andrei Atanov, Alexandra Volokhova, Arsenii Ashukha, Ivan Sosnovik, Dmitry P. Vetrov
Semi-Conditional Normalizing Flows for Semi-Supervised Learning. CoRR (2019)
Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Bayesian Incremental Learning for Deep Neural Networks. CoRR (2018)
Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
Uncertainty Estimation via Stochastic Batch Normalization. CoRR (2018)
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 (2018)
Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
Uncertainty Estimation via Stochastic Batch Normalization. ICLR (Workshop) (2018)
Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Bayesian Incremental Learning for Deep Neural Networks. ICLR (Workshop) (2018)
Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Variational Dropout Sparsifies Deep Neural Networks. CoRR (2017)
Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Structured Bayesian Pruning via Log-Normal Multiplicative Noise. NIPS (2017)
Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Variational Dropout Sparsifies Deep Neural Networks. ICML (2017)