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Publication search results
found 24 matches
- 2024
- Andrey Okhotin, Dmitry Molchanov, Vladimir Arkhipkin, Grigory Bartosh, Viktor Ohanesian, Aibek Alanov, Dmitry P. Vetrov:
Star-Shaped Denoising Diffusion Probabilistic Models (Extended Abstract). KI 2024: 355-359 - 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 abs/2402.19097 (2024) - 2023
- 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 P. Vetrov:
Star-Shaped Denoising Diffusion Probabilistic Models. CoRR abs/2302.05259 (2023) - 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: 1308-1317 - Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov:
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. CoRR abs/2002.06470 (2020) - Dmitry Molchanov, Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry P. Vetrov:
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. CoRR abs/2002.09103 (2020) - Viktor Yanush, Alexander Shekhovtsov, Dmitry Molchanov, Dmitry P. Vetrov:
Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks. CoRR abs/2006.06880 (2020) - 2019
- Dmitry Molchanov, Valery Kharitonov, Artem Sobolev, Dmitry P. Vetrov:
Doubly Semi-Implicit Variational Inference. AISTATS 2019: 2593-2602 - Vera Molchanova, Dmitry Mironenko:
Two-Stage Method for Adaptive Binarization of Raster Engineering Drawings. CMIS 2019: 640-650 - Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Variance Networks: When Expectation Does Not Meet Your Expectations. ICLR (Poster) 2019 - Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov:
Uncertainty Estimation via Stochastic Batch Normalization. ISNN (1) 2019: 261-269 - Vadim Lebedev, Vladimir Ivashkin, Irina Rudenko, Alexander Ganshin, Alexander Molchanov, Sergey Ovcharenko, Ruslan Grokhovetskiy, Ivan Bushmarinov, Dmitry Solomentsev:
Precipitation Nowcasting with Satellite Imagery. KDD 2019: 2680-2688 - Vadim Lebedev, Vladimir Ivashkin, Irina Rudenko, Alexander Ganshin, Alexander Molchanov, Sergey Ovcharenko, Ruslan Grokhovetskiy, Ivan Bushmarinov, Dmitry Solomentsev:
Precipitation Nowcasting with Satellite Imagery. CoRR abs/1905.09932 (2019) - 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 - Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov:
Uncertainty Estimation via Stochastic Batch Normalization. CoRR abs/1802.04893 (2018) - Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Bayesian Incremental Learning for Deep Neural Networks. CoRR abs/1802.07329 (2018) - Dmitry Molchanov, Valery Kharitonov, Artem Sobolev, Dmitry P. Vetrov:
Doubly Semi-Implicit Variational Inference. CoRR abs/1810.02789 (2018) - Valery Kharitonov, Dmitry Molchanov, Dmitry P. Vetrov:
Variational Dropout via Empirical Bayes. CoRR abs/1811.00596 (2018) - 2017
- Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Variational Dropout Sparsifies Deep Neural Networks. ICML 2017: 2498-2507 - Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Structured Bayesian Pruning via Log-Normal Multiplicative Noise. NIPS 2017: 6775-6784 - Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Variational Dropout Sparsifies Deep Neural Networks. CoRR abs/1701.05369 (2017)
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