Dmitry Molchanov

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 20

Top Topics

Stochastic Simulation

Variational Inference

Probabilistic Model

Top Venues

ICLR (Workshop)

Publications

Alexander Shabalin, Viacheslav Meshchaninov, Tingir Badmaev, Dmitry Molchanov, Grigory Bartosh, Sergey Markov, Dmitry P. Vetrov
TEncDM: Understanding the Properties of Diffusion Model in the Space of Language Model Encodings. CoRR (2024)
Andrey Okhotin, Dmitry Molchanov, Vladimir Arkhipkin, Grigory Bartosh, Viktor Ohanesian, Aibek Alanov, Dmitry P. Vetrov
Star-Shaped Denoising Diffusion Probabilistic Models. NeurIPS (2023)
Andrey Okhotin, Dmitry Molchanov, Vladimir Arkhipkin, Grigory Bartosh, Aibek Alanov, Dmitry Vetrov
Star-Shaped Denoising Diffusion Probabilistic Models. CoRR (2023)
Dmitry Molchanov, Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry P. Vetrov
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. CoRR (2020)
Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. CoRR (2020)
Viktor Yanush, Alexander Shekhovtsov, Dmitry Molchanov, Dmitry P. Vetrov
Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks. CoRR (2020)
Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. ICLR (2020)
Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry Molchanov, Dmitry P. Vetrov
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. UAI (2020)
Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
Uncertainty Estimation via Stochastic Batch Normalization. ISNN (1) (2019)
Dmitry Molchanov, Valery Kharitonov, Artem Sobolev, Dmitry P. Vetrov
Doubly Semi-Implicit Variational Inference. AISTATS (2019)
Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Variance Networks: When Expectation Does Not Meet Your Expectations. ICLR (Poster) (2019)
Valery Kharitonov, Dmitry Molchanov, Dmitry P. Vetrov
Variational Dropout via Empirical Bayes. CoRR (2018)
Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Bayesian Incremental Learning for Deep Neural Networks. CoRR (2018)
Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
Uncertainty Estimation via Stochastic Batch Normalization. CoRR (2018)
Dmitry Molchanov, Valery Kharitonov, Artem Sobolev, Dmitry P. Vetrov
Doubly Semi-Implicit Variational Inference. CoRR (2018)
Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
Uncertainty Estimation via Stochastic Batch Normalization. ICLR (Workshop) (2018)
Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Bayesian Incremental Learning for Deep Neural Networks. ICLR (Workshop) (2018)
Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Variational Dropout Sparsifies Deep Neural Networks. CoRR (2017)
Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Structured Bayesian Pruning via Log-Normal Multiplicative Noise. NIPS (2017)
Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
Variational Dropout Sparsifies Deep Neural Networks. ICML (2017)