Dmitry Molchanov
Dmitry Molchanov
Isomorphic Labs
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Variational dropout sparsifies deep neural networks
D Molchanov, A Ashukha, D Vetrov
International conference on machine learning, 2498-2507, 2017
Pitfalls of in-domain uncertainty estimation and ensembling in deep learning
A Ashukha, A Lyzhov, D Molchanov, D Vetrov
arXiv preprint arXiv:2002.06470, 2020
Structured bayesian pruning via log-normal multiplicative noise
K Neklyudov, D Molchanov, A Ashukha, DP Vetrov
Advances in Neural Information Processing Systems 30, 2017
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
Uncertainty estimation via stochastic batch normalization
A Atanov, A Ashukha, D Molchanov, K Neklyudov, D Vetrov
Advances in Neural Networks–ISNN 2019: 16th International Symposium on …, 2019
Doubly semi-implicit variational inference
D Molchanov, V Kharitonov, A Sobolev, D Vetrov
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
Variance networks: When expectation does not meet your expectations
K Neklyudov, D Molchanov, A Ashukha, D Vetrov
arXiv preprint arXiv:1803.03764, 2018
Bayesian incremental learning for deep neural networks
M Kochurov, T Garipov, D Podoprikhin, D Molchanov, A Ashukha, ...
arXiv preprint arXiv:1802.07329, 2018
Variational dropout via empirical bayes
V Kharitonov, D Molchanov, D Vetrov
arXiv preprint arXiv:1811.00596, 5, 2018
Star-shaped denoising diffusion probabilistic models
A Okhotin, D Molchanov, A Vladimir, G Bartosh, V Ohanesian, A Alanov, ...
Advances in Neural Information Processing Systems 36, 2024
Dropout-based automatic relevance determination
D Molchanov, A Ashuha, D Vetrov
Bayesian Deep Learning workshop, NIPS, 2016
Relevance tagging machine
DA Molchanov, DA Kondrashkin, DP Vetrov
Machine Learning and Data Analysis 1 (13), 1877-1887, 2015
TEncDM: Understanding the Properties of Diffusion Model in the Space of Language Model Encodings
A Shabalin, V Meshchaninov, T Badmaev, D Molchanov, G Bartosh, ...
arXiv preprint arXiv:2402.19097, 2024
Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks
V Yanush, A Shekhovtsov, D Molchanov, D Vetrov
arXiv e-prints, arXiv: 2006.06880, 2020
Structured Semi-Implicit Variational Inference
I Molchanova, D Molchanov, N Quadrianto, D Vetrov
Second Symposium on Advances in Approximate Bayesian Inference, 2019
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