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Arsenii Ashukha
Arsenii Ashukha
Isomorphic Labs
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Title
Cited by
Cited by
Year
Variational Dropout Sparsifies Deep Neural Networks
D Molchanov*, A Ashukha*, D Vetrov
Proceedings of the 34th International Conference on Machine Learning (ICML 2017), 2017
9892017
Resolution-robust large mask inpainting with fourier convolutions
R Suvorov, E Logacheva, A Mashikhin, A Remizova, A Ashukha, ...
Proceedings of the IEEE/CVF winter conference on applications of computer …, 2022
5892022
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning
A Ashukha, A Lyzhov, D Molchanov, D Vetrov
International Conference on Learning Representations (ICLR 2020), 2020
3242020
Structured Bayesian Pruning via Log-Normal Multiplicative Noise
K Neklyudov, D Molchanov, A Ashukha, D Vetrov
Advances in Neural Information Processing Systems 30 (NIPS 2017), 2017
2172017
Greedy policy search: A simple baseline for learnable test-time augmentation
A Lyzhov, Y Molchanova, A Ashukha, D Molchanov, D Vetrov
Conference on uncertainty in artificial intelligence, 1308-1317, 2020
602020
Uncertainty Estimation via Stochastic Batch Normalization
A Atanov, A Ashukha, D Molchanov, K Neklyudov, D Vetrov
International Conference on Learning Representations, Workshop Track (ICLR 2018), 2018
582018
The Deep Weight Prior
A Atanov*, A Ashukha*, K Struminsky, D Vetrov, M Welling
International Conference on Learning Representations (ICLR 2019), 2018
442018
Variance Networks: When Expectation Does Not Meet Your Expectations
K Neklyudov*, D Molchanov*, A Ashukha*, D Vetrov
International Conference on Learning Representations (ICLR 2019), 2018
312018
Semi-conditional normalizing flows for semi-supervised learning
A Atanov, A Volokhova, A Ashukha, I Sosnovik, D Vetrov
arXiv preprint arXiv:1905.00505 920, 2019
302019
Bayesian Incremental Learning for Deep Neural Networks
M Kochurov, T Garipov, D Podoprikhin, D Molchanov, A Ashukha, ...
International Conference on Learning Representations, Workshop Track (ICLR 2018), 2018
212018
Automating control of overestimation bias for reinforcement learning
A Kuznetsov, A Grishin, A Tsypin, A Ashukha, A Kadurin, D Vetrov
arXiv preprint arXiv:2110.13523, 2021
132021
Mean embeddings with test-time data augmentation for ensembling of representations
A Ashukha, A Atanov, D Vetrov
arXiv preprint arXiv:2106.08038, 2021
42021
Dropout-based automatic relevance determination
D Molchanov, A Ashuha, D Vetrov
Bayesian Deep Learning Workshop (NeurIPS 2016), 2016
32016
A glimpse of the next generation of AlphaFold
GoogleDeepMind, IsomorphicLabs
https://www.isomorphiclabs.com/articles/a-glimpse-of-the-next-generation-of …, 2023
2023
Unsupervised Domain Adaptation with Shared Latent Dynamics for Reinforcement Learning
E Nikishin, A Ashukha, D Vetrov
Bayesian Deep Learning Workshop (NeurIPS 2019), 2019
2019
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Articles 1–15