Dmitry Molchanov
Dmitry Molchanov
Samsung AI Center Moscow; Higher School of Economics
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TitleCited byYear
Variational dropout sparsifies deep neural networks
D Molchanov, A Ashukha, D Vetrov
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
Structured bayesian pruning via log-normal multiplicative noise
K Neklyudov, D Molchanov, A Ashukha, DP Vetrov
Advances in Neural Information Processing Systems, 6775-6784, 2017
Uncertainty estimation via stochastic batch normalization
A Atanov, A Ashukha, D Molchanov, K Neklyudov, D Vetrov
International Symposium on Neural Networks, 261-269, 2019
Doubly semi-implicit variational inference
D Molchanov, V Kharitonov, A Sobolev, D Vetrov
arXiv preprint arXiv:1810.02789, 2018
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
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
Structured Semi-Implicit Variational Inference
I Molchanova, D Molchanov, N Quadrianto, D Vetrov
Variational Dropout via Empirical Bayes
V Kharitonov, D Molchanov, D Vetrov
arXiv preprint arXiv:1811.00596, 2018
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning
A Ashukha, A Lyzhov, D Molchanov, D Vetrov
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