Dmitry P. Vetrov

179 papers A* 38A 13C 3Misc 3Journal 92Unranked 30

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Streaming Generation of Co-Speech Gestures via Accelerated Rolling Diffusion. AAAI Evgeniia Vu, Andrei Boiarov, Dmitry P. Vetrov
2025	J	`jnl`	Adaptive Destruction Processes for Diffusion Samplers. CoRR Timofei Gritsaev, Nikita Morozov, Kirill Tamogashev, Daniil Tiapkin, Sergey Samsonov, Alexey Naumov, Dmitry P. Vetrov, Nikolay Malkin
2025	J	`jnl`	Can Training Dynamics of Scale-Invariant Neural Networks Be Explained by the Thermodynamics of an Ideal Gas? CoRR Ildus Sadrtdinov, Ekaterina Lobacheva, Ivan Klimov, Mikhail I. Katsnelson, Dmitry P. Vetrov
2025	J	`jnl`	Compressed and Smooth Latent Space for Text Diffusion Modeling. CoRR Viacheslav Meshchaninov, Egor Chimbulatov, Alexander Shabalin, Aleksandr Abramov, Dmitry P. Vetrov
2025	A*	`conf`	Diffusion on Language Model Encodings for Protein Sequence Generation. ICML Viacheslav Meshchaninov, Pavel V. Strashnov, Andrey Shevtsov, Fedor Nikolaev, Nikita Ivanisenko, Olga L. Kardymon, Dmitry P. Vetrov
2025	J	`jnl`	Guided Star-Shaped Masked Diffusion. CoRR Viacheslav Meshchaninov, Egor Shibaev, Artem Makoian, Ivan Klimov, Danil Sheshenya, Andrey Malinin, Nikita Balagansky, Daniil Gavrilov, Aibek Alanov, Dmitry P. Vetrov
2025	J	`jnl`	MiAD: Mirage Atom Diffusion for De Novo Crystal Generation. CoRR Andrey Okhotin, Maksim Nakhodnov, Nikita Kazeev, Andrey E. Ustyuzhanin, Dmitry P. Vetrov
2025	A*	`conf`	SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations. ICML Grigory Bartosh, Dmitry P. Vetrov, Christian A. Naesseth
2025	J	`jnl`	SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations. CoRR Grigory Bartosh, Dmitry P. Vetrov, Christian A. Naesseth
2025	J	`jnl`	SGD as Free Energy Minimization: A Thermodynamic View on Neural Network Training. CoRR Ildus Sadrtdinov, Ivan Klimov, Ekaterina Lobacheva, Dmitry P. Vetrov
2025	J	`jnl`	Smoothie: Smoothing Diffusion on Token Embeddings for Text Generation. CoRR Alexander Shabalin, Viacheslav Meshchaninov, Dmitry P. Vetrov
2025	J	`jnl`	Streaming Generation of Co-Speech Gestures via Accelerated Rolling Diffusion. CoRR Evgeniia Vu, Andrei Boiarov, Dmitry P. Vetrov
2025	A*	`conf`	TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings. AAAI Alexander Shabalin, Viacheslav Meshchaninov, Egor Chimbulatov, Vladislav Lapikov, Roman Kim, Grigory Bartosh, Dmitry Molchanov, Sergey Markov, Dmitry P. Vetrov
2024	A	`conf`	Differentiable Rendering with Reparameterized Volume Sampling. AISTATS Nikita Morozov, Denis Rakitin, Oleg Desheulin, Dmitry P. Vetrov, Kirill Struminsky
2024	J	`jnl`	Diffusion on language model embeddings for protein sequence generation. CoRR Viacheslav Meshchaninov, Pavel V. Strashnov, Andrey Shevtsov, Fedor Nikolaev, Nikita Ivanisenko, Olga L. Kardymon, Dmitry P. Vetrov
2024	A	`conf`	Generative Flow Networks as Entropy-Regularized RL. AISTATS Daniil Tiapkin, Nikita Morozov, Alexey Naumov, Dmitry P. Vetrov
2024	A*	`conf`	Gradual Optimization Learning for Conformational Energy Minimization. ICLR Artem Tsypin, Leonid Ugadiarov, Kuzma Khrabrov, Alexander Telepov, Egor Rumiantsev, Alexey Skrynnik, Aleksandr Panov, Dmitry P. Vetrov, Elena Tutubalina, Artur Kadurin
2024	J	`jnl`	Guide-and-Rescale: Self-Guidance Mechanism for Effective Tuning-Free Real Image Editing. CoRR Vadim Titov, Madina Khalmatova, Alexandra Ivanova, Dmitry P. Vetrov, Aibek Alanov
2024	—	`conf`	Guide-and-Rescale: Self-guidance Mechanism for Effective Tuning-Free Real Image Editing. ECCV (71) Vadim Titov, Madina Khalmatova, Alexandra Ivanova, Dmitry P. Vetrov, Aibek Alanov
2024	A*	`conf`	HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach. NeurIPS Maxim Nikolaev, Mikhail Kuznetsov, Dmitry P. Vetrov, Aibek Alanov
2024	J	`jnl`	HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach. CoRR Maxim Nikolaev, Mikhail Kuznetsov, Dmitry P. Vetrov, Aibek Alanov
2024	J	`jnl`	Improving GFlowNets with Monte Carlo Tree Search. CoRR Nikita Morozov, Daniil Tiapkin, Sergey Samsonov, Alexey Naumov, Dmitry P. Vetrov
2024	A*	`conf`	Neural Diffusion Models. ICML Grigory Bartosh, Dmitry P. Vetrov, Christian A. Naesseth
2024	A*	`conf`	Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling. NeurIPS Grigory Bartosh, Dmitry P. Vetrov, Christian Andersson Naesseth
2024	J	`jnl`	Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling. CoRR Grigory Bartosh, Dmitry P. Vetrov, Christian A. Naesseth
2024	J	`jnl`	Regularized Distribution Matching Distillation for One-step Unpaired Image-to-Image Translation. CoRR Denis Rakitin, Ivan Shchekotov, Dmitry P. Vetrov
2024	Misc	`conf`	Star-Shaped Denoising Diffusion Probabilistic Models (Extended Abstract). KI Andrey Okhotin, Dmitry Molchanov, Vladimir Arkhipkin, Grigory Bartosh, Viktor Ohanesian, Aibek Alanov, Dmitry P. Vetrov
2024	J	`jnl`	TEncDM: Understanding the Properties of Diffusion Model in the Space of Language Model Encodings. CoRR Alexander Shabalin, Viacheslav Meshchaninov, Tingir Badmaev, Dmitry Molchanov, Grigory Bartosh, Sergey Markov, Dmitry P. Vetrov
2024	A*	`conf`	The Devil is in the Details: StyleFeatureEditor for Detail-Rich StyleGAN Inversion and High Quality Image Editing. CVPR Denis Bobkov, Vadim Titov, Aibek Alanov, Dmitry P. Vetrov
2024	J	`jnl`	The Devil is in the Details: StyleFeatureEditor for Detail-Rich StyleGAN Inversion and High Quality Image Editing. CoRR Denis Bobkov, Vadim Titov, Aibek Alanov, Dmitry P. Vetrov
2024	A*	`conf`	Where Do Large Learning Rates Lead Us? NeurIPS Ildus Sadrtdinov, Maxim Kodryan, Eduard Pokonechny, Ekaterina Lobacheva, Dmitry P. Vetrov
2024	J	`jnl`	Where Do Large Learning Rates Lead Us? CoRR Ildus Sadrtdinov, Maxim Kodryan, Eduard Pokonechny, Ekaterina Lobacheva, Dmitry P. Vetrov
2023	J	`jnl`	Differentiable Rendering with Reparameterized Volume Sampling. CoRR Nikita Morozov, Denis Rakitin, Oleg Desheulin, Dmitry P. Vetrov, Kirill Struminsky
2023	A*	`conf`	Entropic Neural Optimal Transport via Diffusion Processes. NeurIPS Nikita Gushchin, Alexander Kolesov, Alexander Korotin, Dmitry P. Vetrov, Evgeny Burnaev
2023	J	`jnl`	Generative Flow Networks as Entropy-Regularized RL. CoRR Daniil Tiapkin, Nikita Morozov, Alexey Naumov, Dmitry P. Vetrov
2023	J	`jnl`	Gradual Optimization Learning for Conformational Energy Minimization. CoRR Artem Tsypin, Leonid Ugadiarov, Kuzma Khrabrov, Manvel Avetisian, Alexander Telepov, Egor Rumiantsev, Alexey Skrynnik, Aleksandr I. Panov, Dmitry P. Vetrov, Elena Tutubalina, Artur Kadurin
2023	Misc	`conf`	HIFI++: A Unified Framework for Bandwidth Extension and Speech Enhancement. ICASSP Pavel Andreev, Aibek Alanov, Oleg Ivanov, Dmitry P. Vetrov
2023	J	`jnl`	Large Learning Rates Improve Generalization: But How Large Are We Talking About? CoRR Ekaterina Lobacheva, Eduard Pockonechnyy, Maxim Kodryan, Dmitry P. Vetrov
2023	A	`conf`	MARS: Masked Automatic Ranks Selection in Tensor Decompositions. AISTATS Maxim Kodryan, Dmitry Kropotov, Dmitry P. Vetrov
2023	J	`jnl`	Neural Diffusion Models. CoRR Grigory Bartosh, Dmitry P. Vetrov, Christian A. Naesseth
2023	A*	`conf`	Star-Shaped Denoising Diffusion Probabilistic Models. NeurIPS Andrey Okhotin, Dmitry Molchanov, Vladimir Arkhipkin, Grigory Bartosh, Viktor Ohanesian, Aibek Alanov, Dmitry P. Vetrov
2023	J	`jnl`	Star-Shaped Denoising Diffusion Probabilistic Models. CoRR Andrey Okhotin, Dmitry Molchanov, Vladimir Arkhipkin, Grigory Bartosh, Aibek Alanov, Dmitry P. Vetrov
2023	A*	`conf`	StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation. ICCV Aibek Alanov, Vadim Titov, Maksim Nakhodnov, Dmitry P. Vetrov
2023	A*	`conf`	To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning. NeurIPS Ildus Sadrtdinov, Dmitrii Pozdeev, Dmitry P. Vetrov, Ekaterina Lobacheva
2023	J	`jnl`	To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning. CoRR Ildus Sadrtdinov, Dmitrii Pozdeev, Dmitry P. Vetrov, Ekaterina Lobacheva
2023	A	`conf`	UnDiff: Unsupervised Voice Restoration with Unconditional Diffusion Model. INTERSPEECH Anastasiia Iashchenko, Pavel Andreev, Ivan Shchekotov, Nicholas Babaev, Dmitry P. Vetrov
2023	J	`jnl`	UnDiff: Unsupervised Voice Restoration with Unconditional Diffusion Model. CoRR Anastasiia Iashchenko, Pavel Andreev, Ivan Shchekotov, Nicholas Babaev, Dmitry P. Vetrov
2022	J	`jnl`	Entropic Neural Optimal Transport via Diffusion Processes. CoRR Nikita Gushchin, Alexander Kolesov, Alexander Korotin, Dmitry P. Vetrov, Evgeny Burnaev
2022	A	`conf`	FFC-SE: Fast Fourier Convolution for Speech Enhancement. INTERSPEECH Ivan Shchekotov, Pavel K. Andreev, Oleg Ivanov, Aibek Alanov, Dmitry P. Vetrov
2022	J	`jnl`	FFC-SE: Fast Fourier Convolution for Speech Enhancement. CoRR Ivan Shchekotov, Pavel Andreev, Oleg Ivanov, Aibek Alanov, Dmitry P. Vetrov
2022	J	`jnl`	HiFi++: a Unified Framework for Neural Vocoding, Bandwidth Extension and Speech Enhancement. CoRR Pavel Andreev, Aibek Alanov, Oleg Ivanov, Dmitry P. Vetrov
2022	A*	`conf`	HyperDomainNet: Universal Domain Adaptation for Generative Adversarial Networks. NeurIPS Aibek Alanov, Vadim Titov, Dmitry P. Vetrov
2022	J	`jnl`	HyperDomainNet: Universal Domain Adaptation for Generative Adversarial Networks. CoRR Aibek Alanov, Vadim Titov, Dmitry P. Vetrov
2022	J	`jnl`	StyleDomain: Analysis of StyleSpace for Domain Adaptation of StyleGAN. CoRR Aibek Alanov, Vadim Titov, Maksim Nakhodnov, Dmitry P. Vetrov
2022	A*	`conf`	Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes. NeurIPS Maxim Kodryan, Ekaterina Lobacheva, Maksim Nakhodnov, Dmitry P. Vetrov
2022	J	`jnl`	Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes. CoRR Maxim Kodryan, Ekaterina Lobacheva, Maksim Nakhodnov, Dmitry P. Vetrov
2021	J	`jnl`	Automating Control of Overestimation Bias for Continuous Reinforcement Learning. CoRR Arsenii Kuznetsov, Alexander Grishin, Artem Tsypin, Arsenii Ashukha, Dmitry P. Vetrov
2021	A*	`conf`	Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces. NeurIPS Kirill Struminsky, Artyom Gadetsky, Denis Rakitin, Danil Karpushkin, Dmitry P. Vetrov
2021	J	`jnl`	Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces. CoRR Kirill Struminsky, Artyom Gadetsky, Denis Rakitin, Danil Karpushkin, Dmitry P. Vetrov
2021	J	`jnl`	Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems. CoRR Evgeny Bobrov, Sergey Troshin, Nadezhda Chirkova, Ekaterina Lobacheva, Sviatoslav Panchenko, Dmitry P. Vetrov, Dmitry Kropotov
2021	J	`jnl`	Mean Embeddings with Test-Time Data Augmentation for Ensembling of Representations. CoRR Arsenii Ashukha, Andrei Atanov, Dmitry P. Vetrov
2021	A*	`conf`	On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay. NeurIPS Ekaterina Lobacheva, Maxim Kodryan, Nadezhda Chirkova, Andrey Malinin, Dmitry P. Vetrov
2021	J	`jnl`	On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay. CoRR Ekaterina Lobacheva, Maxim Kodryan, Nadezhda Chirkova, Andrey Malinin, Dmitry P. Vetrov
2021	J	`jnl`	Quantization of Generative Adversarial Networks for Efficient Inference: a Methodological Study. CoRR Pavel Andreev, Alexander Fritzler, Dmitry P. Vetrov
2021	J	`jnl`	Towards Practical Credit Assignment for Deep Reinforcement Learning. CoRR Vyacheslav Alipov, Riley Simmons-Edler, Nikita Putintsev, Pavel Kalinin, Dmitry P. Vetrov
2021	J	`jnl`	Variational Autoencoders for Studying the Manifold of Precoding Matrices with High Spectral Efficiency. CoRR Evgeny Bobrov, Alexander Markov, Dmitry P. Vetrov
2020	A*	`conf`	Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics. ICML Arsenii Kuznetsov, Pavel Shvechikov, Alexander Grishin, Dmitry P. Vetrov
2020	J	`jnl`	Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics. CoRR Arsenii Kuznetsov, Pavel Shvechikov, Alexander Grishin, Dmitry P. Vetrov
2020	J	`jnl`	Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones? CoRR Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov
2020	A	`conf`	Deterministic Decoding for Discrete Data in Variational Autoencoders. AISTATS Daniil Polykovskiy, Dmitry P. Vetrov
2020	J	`jnl`	Deterministic Decoding for Discrete Data in Variational Autoencoders. CoRR Daniil Polykovskiy, Dmitry P. Vetrov
2020	A	`conf`	Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. UAI Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry Molchanov, Dmitry P. Vetrov
2020	J	`jnl`	Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. CoRR Dmitry Molchanov, Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry P. Vetrov
2020	A*	`conf`	Involutive MCMC: a Unifying Framework. ICML Kirill Neklyudov, Max Welling, Evgenii Egorov, Dmitry P. Vetrov
2020	J	`jnl`	Involutive MCMC: a Unifying Framework. CoRR Kirill Neklyudov, Max Welling, Evgenii Egorov, Dmitry P. Vetrov
2020	A*	`conf`	Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution. AAAI Artyom Gadetsky, Kirill Struminsky, Christopher Robinson, Novi Quadrianto, Dmitry P. Vetrov
2020	J	`jnl`	MARS: Masked Automatic Ranks Selection in Tensor Decompositions. CoRR Maxim Kodryan, Dmitry Kropotov, Dmitry P. Vetrov
2020	A*	`conf`	On Power Laws in Deep Ensembles. NeurIPS Ekaterina Lobacheva, Nadezhda Chirkova, Maxim Kodryan, Dmitry P. Vetrov
2020	J	`jnl`	On Power Laws in Deep Ensembles. CoRR Ekaterina Lobacheva, Nadezhda Chirkova, Maxim Kodryan, Dmitry P. Vetrov
2020	A*	`conf`	Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. ICLR Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov
2020	J	`jnl`	Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. CoRR Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov
2020	J	`jnl`	Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks. CoRR Viktor Yanush, Alexander Shekhovtsov, Dmitry Molchanov, Dmitry P. Vetrov
2020	J	`jnl`	Stochasticity in Neural ODEs: An Empirical Study. CoRR Viktor Oganesyan, Alexandra Volokhova, Dmitry P. Vetrov
2020	A*	`conf`	Structured Sparsification of Gated Recurrent Neural Networks. AAAI Ekaterina Lobacheva, Nadezhda Chirkova, Alexander Markovich, Dmitry P. Vetrov
2020	—	`conf`	User-controllable Multi-texture Synthesis with Generative Adversarial Networks. VISIGRAPP (4: VISAPP) Aibek Alanov, Max Kochurov, Denis Volkhonskiy, Daniil Yashkov, Evgeny Burnaev, Dmitry P. Vetrov
2019	A*	`conf`	A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models. NeurIPS Maksim Kuznetsov, Daniil Polykovskiy, Dmitry P. Vetrov, Alexander Zhebrak
2019	J	`jnl`	A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models. CoRR Maksim Kuznetsov, Daniil Polykovskiy, Dmitry P. Vetrov, Alexander Zhebrak
2019	A*	`conf`	A Simple Baseline for Bayesian Uncertainty in Deep Learning. NeurIPS Wesley J. Maddox, Pavel Izmailov, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson
2019	J	`jnl`	A Simple Baseline for Bayesian Uncertainty in Deep Learning. CoRR Wesley J. Maddox, Timur Garipov, Pavel Izmailov, Dmitry P. Vetrov, Andrew Gordon Wilson
2019	Misc	`conf`	A Simple Method to Evaluate Support Size and Non-uniformity of a Decoder-Based Generative Model. AIST Kirill Struminsky, Dmitry P. Vetrov
2019	A	`conf`	Doubly Semi-Implicit Variational Inference. AISTATS Dmitry Molchanov, Valery Kharitonov, Artem Sobolev, Dmitry P. Vetrov
2019	—	`conf`	Efficient Language Modeling with Automatic Relevance Determination in Recurrent Neural Networks. RepL4NLP@ACL Maxim Kodryan, Artem M. Grachev, Dmitry I. Ignatov, Dmitry P. Vetrov
2019	A*	`conf`	Importance Weighted Hierarchical Variational Inference. NeurIPS Artem Sobolev, Dmitry P. Vetrov
2019	J	`jnl`	Importance Weighted Hierarchical Variational Inference. CoRR Artem Sobolev, Dmitry P. Vetrov
2019	J	`jnl`	Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution. CoRR Artyom Gadetsky, Kirill Struminsky, Christopher Robinson, Novi Quadrianto, Dmitry P. Vetrov
2019	J	`jnl`	MLRG Deep Curvature. CoRR Diego Granziol, Xingchen Wan, Timur Garipov, Dmitry P. Vetrov, Stephen Roberts
2019	J	`jnl`	Semi-Conditional Normalizing Flows for Semi-Supervised Learning. CoRR Andrei Atanov, Alexandra Volokhova, Arsenii Ashukha, Ivan Sosnovik, Dmitry P. Vetrov
2019	J	`jnl`	Structured Sparsification of Gated Recurrent Neural Networks. CoRR Ekaterina Lobacheva, Nadezhda Chirkova, Alexander Markovich, Dmitry P. Vetrov
2019	A	`conf`	Subspace Inference for Bayesian Deep Learning. UAI Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson
2019	J	`jnl`	Subspace Inference for Bayesian Deep Learning. CoRR Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson
2019	—	`conf`	The Deep Weight Prior. ICLR (Poster) Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling
2019	A*	`conf`	The Implicit Metropolis-Hastings Algorithm. NeurIPS Kirill Neklyudov, Evgenii Egorov, Dmitry P. Vetrov
2019	J	`jnl`	The Implicit Metropolis-Hastings Algorithm. CoRR Kirill Neklyudov, Evgenii Egorov, Dmitry P. Vetrov
2019	—	`conf`	Uncertainty Estimation via Stochastic Batch Normalization. ISNN (1) Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
2019	J	`jnl`	User-Controllable Multi-Texture Synthesis with Generative Adversarial Networks. CoRR Aibek Alanov, Max Kochurov, Denis Volkhonskiy, Daniil Yashkov, Evgeny Burnaev, Dmitry P. Vetrov
2019	—	`conf`	Variance Networks: When Expectation Does Not Meet Your Expectations. ICLR (Poster) Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2019	—	`conf`	Variational Autoencoder with Arbitrary Conditioning. ICLR (Poster) Oleg Ivanov, Michael Figurnov, Dmitry P. Vetrov
2018	A	`conf`	Averaging Weights Leads to Wider Optima and Better Generalization. UAI Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson
2018	J	`jnl`	Averaging Weights Leads to Wider Optima and Better Generalization. CoRR Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson
2018	A*	`conf`	Bayesian Compression for Natural Language Processing. EMNLP Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov
2018	J	`jnl`	Bayesian Compression for Natural Language Processing. CoRR Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov
2018	—	`conf`	Bayesian Incremental Learning for Deep Neural Networks. ICLR (Workshop) Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2018	J	`jnl`	Bayesian Incremental Learning for Deep Neural Networks. CoRR Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2018	J	`jnl`	Bayesian Sparsification of Gated Recurrent Neural Networks. CoRR Ekaterina Lobacheva, Nadezhda Chirkova, Dmitry P. Vetrov
2018	—	`conf`	Conditional Generators of Words Definitions. ACL (2) Artyom Gadetsky, Ilya Yakubovskiy, Dmitry P. Vetrov
2018	J	`jnl`	Conditional Generators of Words Definitions. CoRR Artyom Gadetsky, Ilya Yakubovskiy, Dmitry P. Vetrov
2018	J	`jnl`	Doubly Semi-Implicit Variational Inference. CoRR Dmitry Molchanov, Valery Kharitonov, Artem Sobolev, Dmitry P. Vetrov
2018	A	`conf`	Few-shot Generative Modelling with Generative Matching Networks. AISTATS Sergey Bartunov, Dmitry P. Vetrov
2018	A*	`conf`	Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs. NeurIPS Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P. Vetrov, Andrew Gordon Wilson
2018	J	`jnl`	Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs. CoRR Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P. Vetrov, Andrew Gordon Wilson
2018	J	`jnl`	Metropolis-Hastings view on variational inference and adversarial training. CoRR Kirill Neklyudov, Pavel Shvechikov, Dmitry P. Vetrov
2018	J	`jnl`	Pairwise Augmented GANs with Adversarial Reconstruction Loss. CoRR Aibek Alanov, Max Kochurov, Daniil Yashkov, Dmitry P. Vetrov
2018	C	`conf`	ReSet: Learning Recurrent Dynamic Routing in ResNet-like Neural Networks. ACML Iurii Kemaev, Daniil Polykovskiy, Dmitry P. Vetrov
2018	J	`jnl`	ReSet: Learning Recurrent Dynamic Routing in ResNet-like Neural Networks. CoRR Iurii Kemaev, Daniil Polykovskiy, Dmitry P. Vetrov
2018	J	`jnl`	The Deep Weight Prior. Modeling a prior distribution for CNNs using generative models. CoRR Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling
2018	—	`conf`	Uncertainty Estimation via Stochastic Batch Normalization. ICLR (Workshop) Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
2018	J	`jnl`	Uncertainty Estimation via Stochastic Batch Normalization. CoRR Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
2018	J	`jnl`	Universal Conditional Machine. CoRR Oleg Ivanov, Michael Figurnov, Dmitry P. Vetrov
2018	J	`jnl`	Variational Dropout via Empirical Bayes. CoRR Valery Kharitonov, Dmitry Molchanov, Dmitry P. Vetrov
2017	J	`jnl`	Bayesian Sparsification of Recurrent Neural Networks. CoRR Ekaterina Lobacheva, Nadezhda Chirkova, Dmitry P. Vetrov
2017	—	`conf`	Fast Adaptation in Generative Models with Generative Matching Networks. ICLR (Workshop) Sergey Bartunov, Dmitry P. Vetrov
2017	J	`jnl`	Probabilistic Adaptive Computation Time. CoRR Michael Figurnov, Artem Sobolev, Dmitry P. Vetrov
2017	A*	`conf`	Spatially Adaptive Computation Time for Residual Networks. CVPR Michael Figurnov, Maxwell D. Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry P. Vetrov, Ruslan Salakhutdinov
2017	—	`conf`	Structured Bayesian Pruning via Log-Normal Multiplicative Noise. NIPS Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2017	A*	`conf`	Variational Dropout Sparsifies Deep Neural Networks. ICML Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2017	J	`jnl`	Variational Dropout Sparsifies Deep Neural Networks. CoRR Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov
2016	—	`conf`	A new approach for sparse Bayesian channel estimation in SCMA uplink systems. WCSP Kirill Struminsky, Stanislav Kruglik, Dmitry P. Vetrov, Ivan V. Oseledets
2016	A	`conf`	Breaking Sticks and Ambiguities with Adaptive Skip-gram. AISTATS Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin, Dmitry P. Vetrov
2016	A	`conf`	Deep Part-Based Generative Shape Model with Latent Variables. BMVC Alexander Kirillov, Mikhail Gavrikov, Ekaterina Lobacheva, Anton Osokin, Dmitry P. Vetrov
2016	J	`jnl`	Fast Adaptation in Generative Models with Generative Matching Networks. CoRR Sergey Bartunov, Dmitry P. Vetrov
2016	J	`jnl`	GTApprox: Surrogate modeling for industrial design. Adv. Eng. Softw. Mikhail Belyaev, Evgeny Burnaev, Ermek Kapushev, Maxim Panov, Pavel V. Prikhodko, Dmitry P. Vetrov, Dmitry Yarotsky
2016	J	`jnl`	GTApprox: surrogate modeling for industrial design. CoRR Mikhail Belyaev, Evgeny Burnaev, Ermek Kapushev, Maxim Panov, Pavel V. Prikhodko, Dmitry P. Vetrov, Dmitry Yarotsky
2016	—	`conf`	PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions. NIPS Mikhail Figurnov, Aizhan Ibraimova, Dmitry P. Vetrov, Pushmeet Kohli
2016	J	`jnl`	Robust Variational Inference. CoRR Michael Figurnov, Kirill Struminsky, Dmitry P. Vetrov
2016	J	`jnl`	Spatially Adaptive Computation Time for Residual Networks. CoRR Michael Figurnov, Maxwell D. Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry P. Vetrov, Ruslan Salakhutdinov
2016	J	`jnl`	Ultimate tensorization: compressing convolutional and FC layers alike. CoRR Timur Garipov, Dmitry Podoprikhin, Alexander Novikov, Dmitry P. Vetrov
2015	J	`jnl`	Breaking Sticks and Ambiguities with Adaptive Skip-gram. CoRR Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin, Dmitry P. Vetrov
2015	A*	`conf`	Inferring M-Best Diverse Labelings in a Single One. ICCV Alexander Kirillov, Bogdan Savchynskyy, Dmitrij Schlesinger, Dmitry P. Vetrov, Carsten Rother
2015	—	`conf`	M-Best-Diverse Labelings for Submodular Energies and Beyond. NIPS Alexander Kirillov, Dmytro Shlezinger, Dmitry P. Vetrov, Carsten Rother, Bogdan Savchynskyy
2015	J	`jnl`	PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions. CoRR Michael Figurnov, Dmitry P. Vetrov, Pushmeet Kohli
2015	J	`jnl`	Submodular Relaxation for Inference in Markov Random Fields. IEEE Trans. Pattern Anal. Mach. Intell. Anton Osokin, Dmitry P. Vetrov
2015	J	`jnl`	Submodular relaxation for inference in Markov random fields. CoRR Anton Osokin, Dmitry P. Vetrov
2015	—	`conf`	Tensorizing Neural Networks. NIPS Alexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry P. Vetrov
2015	J	`jnl`	Tensorizing Neural Networks. CoRR Alexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry P. Vetrov
2014	—	`conf`	Multi-utility Learning: Structured-Output Learning with Multiple Annotation-Specific Loss Functions. EMMCVPR Roman Shapovalov, Dmitry P. Vetrov, Anton Osokin, Pushmeet Kohli
2014	J	`jnl`	Multi-utility Learning: Structured-output Learning with Multiple Annotation-specific Loss Functions. CoRR Roman Shapovalov, Dmitry P. Vetrov, Anton Osokin, Pushmeet Kohli
2014	A*	`conf`	Putting MRFs on a Tensor Train. ICML Alexander Novikov, Anton Rodomanov, Anton Osokin, Dmitry P. Vetrov
2014	A*	`conf`	Variational Inference for Sequential Distance Dependent Chinese Restaurant Process. ICML Sergey Bartunov, Dmitry P. Vetrov
2013	—	`conf`	Learning a Model for Shape-Constrained Image Segmentation from Weakly Labeled Data. EMMCVPR Boris Yangel, Dmitry P. Vetrov
2013	A*	`conf`	Spatial Inference Machines. CVPR Roman Shapovalov, Dmitry P. Vetrov, Pushmeet Kohli
2013	—	`conf`	Машинное обучение - состояние и перспективы (Machine Learning: State of the Art and Perspectives). RCDL Dmitry P. Vetrov
2012	—	`conf`	Submodular Relaxation for MRFs with High-Order Potentials. ECCV Workshops (3) Anton Osokin, Dmitry P. Vetrov
2011	J	`jnl`	Automated atlas-based segmentation of NISSL-stained mouse brain sections using supervised learning. Program. Comput. Softw. Olga V. Senyukova, A. S. Lukin, Dmitry P. Vetrov
2011	—	`conf`	Image Segmentation with a Shape Prior Based on Simplified Skeleton. EMMCVPR Boris Yangel, Dmitry P. Vetrov
2011	J	`jnl`	Submodular Decomposition Framework for Inference in Associative Markov Networks with Global Constraints CoRR Anton Osokin, Dmitry P. Vetrov, Vladimir Kolmogorov
2011	A*	`conf`	Submodular decomposition framework for inference in associative Markov networks with global constraints. CVPR Anton Osokin, Dmitry P. Vetrov, Vladimir Kolmogorov
2010	—	`conf`	An Interactive Method of Anatomical Segmentation and Gene Expression Estimation for an Experimental Mouse Brain Slice. CIBB Anton Osokin, Dmitry P. Vetrov, Alexey Lebedev, Vladimir Galatenko, Dmitry Kropotov, Konstantin V. Anokhin
2010	C	`conf`	Variational Relevance Vector Machine for Tabular Data. ACML Dmitry Kropotov, Dmitry P. Vetrov, Lior Wolf, Tal Hassner
2009	—	`conf`	3-D Mouse Brain Model Reconstruction from a Sequence of 2-D Slices in Application to Allen Brain Atlas. CIBB Anton Osokin, Dmitry P. Vetrov, Dmitry Kropotov
2009	—	`conf`	ODDboost: Incorporating Posterior Estimates into AdaBoost. MLDM Olga Barinova, Dmitry P. Vetrov
2007	—	`conf`	Fuzzy Rules Generation Method for Pattern Recognition Problems. WILF Dmitry Kropotov, Dmitry P. Vetrov
2007	A*	`conf`	On one method of non-diagonal regularization in sparse Bayesian learning. ICML Dmitry Kropotov, Dmitry P. Vetrov
2006	J	`jnl`	Evaluation of Stability of k-Means Cluster Ensembles with Respect to Random Initialization. IEEE Trans. Pattern Anal. Mach. Intell. Ludmila I. Kuncheva, Dmitry P. Vetrov
2006	—	`conf`	On Kernel Selection in Relevance Vector Machines Using Stability Principle. ICPR (4) Dmitry Kropotov, Nikita Ptashko, Oleg Vasiliev, Dmitry P. Vetrov
2006	—	`conf`	The Use of Stability Principle for Kernel Determination in Relevance Vector Machines. ICONIP (1) Dmitry Kropotov, Dmitry P. Vetrov, Nikita Ptashko, Oleg Vasiliev
2005	C	`conf`	The Use of Bayesian Framework for Kernel Selection in Vector Machines Classifiers. CIARP Dmitry Kropotov, Nikita Ptashko, Dmitry P. Vetrov
2004	—	`conf`	An Algorithm for Rule Generation in Fuzzy Expert Systems. ICPR (1) Dmitry Kropotov, Dmitry P. Vetrov
2004	—	`conf`	Data Dependent Classifier Fusion for Construction of Stable Effective Algorithms. ICPR (1) Dmitry P. Vetrov, Dmitry Kropotov
2003	—	`conf`	One Approach to Fuzzy Expert Systems Construction. ICEIS (2) Dmitry Kropotov, Dmitry P. Vetrov