Variational Dropout Sparsifies Deep Neural Networks. - Dmitry Molchanov; Arsenii Ashukha; Dmitry P. Vetrov (ICML, 2017)

Structured Bayesian Pruning via Log-Normal Multiplicative Noise. - Kirill Neklyudov; Dmitry Molchanov; Arsenii Ashukha; Dmitry P. Vetrov (NIPS, 2017)

Uncertainty Estimation via Stochastic Batch Normalization. - Andrei Atanov; Arsenii Ashukha; Dmitry Molchanov; Kirill Neklyudov; Dmitry P. Vetrov (ICLR (Workshop), 2018)

Bayesian Incremental Learning for Deep Neural Networks. - Max Kochurov; Timur Garipov; Dmitry Podoprikhin; Dmitry Molchanov; Arsenii Ashukha; Dmitry P. Vetrov (ICLR (Workshop), 2018)

Variational Dropout via Empirical Bayes. - Valery Kharitonov; Dmitry Molchanov; Dmitry P. Vetrov (CoRR, 2018)

Doubly Semi-Implicit Variational Inference. - Dmitry Molchanov; Valery Kharitonov; Artem Sobolev; Dmitry P. Vetrov (AISTATS, 2019)

Variance Networks: When Expectation Does Not Meet Your Expectations. - Kirill Neklyudov; Dmitry Molchanov; Arsenii Ashukha; Dmitry P. Vetrov (ICLR (Poster), 2019)

Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. - Arsenii Ashukha; Alexander Lyzhov; Dmitry Molchanov; Dmitry P. Vetrov (ICLR, 2020)

Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. - Alexander Lyzhov; Yuliya Molchanova; Arsenii Ashukha; Dmitry Molchanov; Dmitry P. Vetrov (UAI, 2020)

Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks. - Viktor Yanush; Alexander Shekhovtsov; Dmitry Molchanov; Dmitry P. Vetrov (CoRR, 2020)

Star-Shaped Denoising Diffusion Probabilistic Models. - Andrey Okhotin; Dmitry Molchanov; Vladimir Arkhipkin; Grigory Bartosh; Viktor Ohanesian; Aibek Alanov; Dmitry P. Vetrov (NeurIPS, 2023)

Star-Shaped Denoising Diffusion Probabilistic Models. - Andrey Okhotin; Dmitry Molchanov; Vladimir Arkhipkin; Grigory Bartosh; Aibek Alanov; Dmitry P. Vetrov (CoRR, 2023)

Star-Shaped Denoising Diffusion Probabilistic Models (Extended Abstract). - Andrey Okhotin; Dmitry Molchanov; Vladimir Arkhipkin; Grigory Bartosh; Viktor Ohanesian; Aibek Alanov; Dmitry P. Vetrov (KI, 2024)

TEncDM: Understanding the Properties of Diffusion Model in the Space of Language Model Encodings. - Alexander Shabalin; Viacheslav Meshchaninov; Tingir Badmaev; Dmitry Molchanov; Grigory Bartosh; Sergey Markov; Dmitry P. Vetrov (CoRR, 2024)

TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings. - Alexander Shabalin; Viacheslav Meshchaninov; Egor Chimbulatov; Vladislav Lapikov; Roman Kim; Grigory Bartosh; Dmitry Molchanov; Sergey Markov; Dmitry P. Vetrov (AAAI, 2025)