Arsenii Ashukha

20 papers A* 2A 2Journal 10Unranked 6

Year	Rank	Type	Title / Venue / Authors
2022	A	`conf`	Resolution-robust Large Mask Inpainting with Fourier Convolutions. WACV Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, Victor Lempitsky
2021	J	`jnl`	Automating Control of Overestimation Bias for Continuous Reinforcement Learning. CoRR Arsenii Kuznetsov, Alexander Grishin, Artem Tsypin, Arsenii Ashukha, Dmitry P. Vetrov
2021	J	`jnl`	Mean Embeddings with Test-Time Data Augmentation for Ensembling of Representations. CoRR Arsenii Ashukha, Andrei Atanov, Dmitry P. Vetrov
2021	J	`jnl`	Resolution-robust Large Mask Inpainting with Fourier Convolutions. CoRR Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, Victor Lempitsky
2020	A	`conf`	Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. UAI Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry Molchanov, Dmitry P. Vetrov
2020	J	`jnl`	Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. CoRR Dmitry Molchanov, Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry P. Vetrov
2020	A*	`conf`	Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. ICLR Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov
2020	J	`jnl`	Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. CoRR Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov
2019	J	`jnl`	Semi-Conditional Normalizing Flows for Semi-Supervised Learning. CoRR Andrei Atanov, Alexandra Volokhova, Arsenii Ashukha, Ivan Sosnovik, Dmitry P. Vetrov
2019	—	`conf`	The Deep Weight Prior. ICLR (Poster) Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling
2019	—	`conf`	Uncertainty Estimation via Stochastic Batch Normalization. ISNN (1) Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
2019	—	`conf`	Variance Networks: When Expectation Does Not Meet Your Expectations. ICLR (Poster) Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2018	—	`conf`	Bayesian Incremental Learning for Deep Neural Networks. ICLR (Workshop) Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2018	J	`jnl`	Bayesian Incremental Learning for Deep Neural Networks. CoRR Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2018	J	`jnl`	The Deep Weight Prior. Modeling a prior distribution for CNNs using generative models. CoRR Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling
2018	—	`conf`	Uncertainty Estimation via Stochastic Batch Normalization. ICLR (Workshop) Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
2018	J	`jnl`	Uncertainty Estimation via Stochastic Batch Normalization. CoRR Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
2017	—	`conf`	Structured Bayesian Pruning via Log-Normal Multiplicative Noise. NIPS Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2017	A*	`conf`	Variational Dropout Sparsifies Deep Neural Networks. ICML Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2017	J	`jnl`	Variational Dropout Sparsifies Deep Neural Networks. CoRR Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov