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Vetrov, Dmitry

  1. Averaging Weights Leads to Wider Optima and Better Generalization
    2018/03/14 by Pavel Izmailov, D. A. Podoprikhin, Izmailov, Pavel +7 · 142 citations
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  2. Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
    2018/02/27 by Timur Garipov, Pavel Izmailov, Garipov, Timur +7 · 72 citations
    Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #Adversarial Robustness in Machine Learning
  3. A Simple Baseline for Bayesian Uncertainty in Deep Learning
    2019/02/07 by Wesley J. Maddox, Timur Garipov, Maddox, Wesley +7 · 86 citations
    Computer Science · #Gaussian Processes and Bayesian Inference #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning
  4. Tensorizing Neural Networks
    2015/09/22 by Alexander Novikov, Novikov, Alexander, Dmitry Podoprikhin +5 · 49 citations
    Computer Science · Mathematics · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural and Evolutionary Computing (cs.NE) #Parallel Computing and Optimization Techniques #Stochastic Gradient Optimization Techniques #Tensor decomposition and applications
  5. Variational Dropout Sparsifies Deep Neural Networks
    2017/01/19 by Dmitry Molchanov, Arsenii Ashukha, Molchanov, Dmitry +3 · 59 citations
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Machine Learning and Data Classification
  6. Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
    2020/05/08 by Kuznetsov, Arsenii, Shvechikov, Pavel, Grishin, Alexander +1 · 21 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  7. Spatially Adaptive Computation Time for Residual Networks
    2016/12/07 by Michael Figurnov, Maxwell D. Collins, Figurnov, Michael +11 · 13 citations
    Computer Science · #Visual Attention and Saliency Detection #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning
  8. Subspace Inference for Bayesian Deep Learning
    2019/07/17 by Pavel Izmailov, Wesley J. Maddox, Izmailov, Pavel +9 · 9 citations
    Computer Science · #Gaussian Processes and Bayesian Inference #Anomaly Detection Techniques and Applications #Generative Adversarial Networks and Image Synthesis
  9. Greedy Policy Search: A Simple Baseline for Learnable Test-Time\n Augmentation
    2020/02/20 by Dmitry Molchanov, Molchanov, Dmitry, Alexander Lyzhov +7 · 7 citations
    Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Multimodal Machine Learning Applications
  10. Generative Flow Networks as Entropy-Regularized RL
    2023/10/19 by Daniil Tiapkin, Tiapkin, Daniil, Н. Ф. Морозов +5 · 12 citations
    Computer Science · #Reinforcement Learning in Robotics #Explainable Artificial Intelligence (XAI)
  11. Variational Autoencoder with Arbitrary Conditioning
    2018/06/06 by Ivanov, Oleg, Figurnov, Michael, Vetrov, Dmitry · 5 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  12. Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling
    2024/04/19 by Grigory Bartosh, Bartosh, Grigory, Dmitry Vetrov +3 · 11 citations
    Physics and Astronomy · #Model Reduction and Neural Networks
  13. Entropic Neural Optimal Transport via Diffusion Processes
    2022/11/02 by Nikita Gushchin, A. K. Kolesov, Gushchin, Nikita +7 · 7 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications #Stochastic Gradient Optimization Techniques
  14. SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations
    2025/02/04 by Grigory Bartosh, Bartosh, Grigory, Dmitry Vetrov +3 · 2 voices · 6 citations
    Computer Science · #Gaussian Processes and Bayesian Inference #Machine Learning and Data Classification #Bayesian Modeling and Causal Inference
  15. UnDiff: Unsupervised Voice Restoration with Unconditional Diffusion Model
    2023/06/01 by Iashchenko, Anastasiia, Andreev, Pavel, Shchekotov, Ivan +2 · 5 citations
    #Artificial Intelligence (cs.AI) #Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #Sound (cs.SD) #electronic engineering #information engineering
  16. Star-Shaped Denoising Diffusion Probabilistic Models
    2023/02/10 by Andrey Okhotin, Okhotin, Andrey, Dmitry Molchanov +10 · 5 citations
    Computer Science · #Generative Adversarial Networks and Image Synthesis #Bayesian Methods and Mixture Models #Machine Learning in Healthcare
  17. TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings
    2024/02/29 by Shabalin, Alexander, Meshchaninov, Viacheslav, Chimbulatov, Egor +6 · 5 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences #I.2 #I.7
  18. Neural Diffusion Models
    2023/10/12 by Bartosh, Grigory, Vetrov, Dmitry, Naesseth, Christian A. · 4 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  19. Conditional Generators of Words Definitions
    2018/06/26 by Gadetsky, Artyom, Yakubovskiy, Ilya, Vetrov, Dmitry · 2 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences
  20. On Power Laws in Deep Ensembles
    2020/07/16 by Lobacheva, Ekaterina, Chirkova, Nadezhda, Kodryan, Maxim +1 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  21. Cosmos: Compressed and Smooth Latent Space for Text Diffusion Modeling
    2025/06/26 by Viacheslav Meshchaninov, Meshchaninov, Viacheslav, Egor Chimbulatov +6 · 7 citations
    Computer Science · #Topic Modeling #Natural Language Processing Techniques #Speech Recognition and Synthesis
  22. Semi-Conditional Normalizing Flows for Semi-Supervised Learning
    2019/05/01 by Andrei Atanov, Alexandra Volokhova, Atanov, Andrei +7 · 3 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #Generative Adversarial Networks and Image Synthesis #Anomaly Detection Techniques and Applications
  23. PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions
    2015/04/30 by Figurnov, Michael, Ibraimova, Aijan, Vetrov, Dmitry +1 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  24. Guide-and-Rescale: Self-Guidance Mechanism for Effective Tuning-Free Real Image Editing
    2024/09/02 by Titov, Vadim, Khalmatova, Madina, Ivanova, Alexandra +2 · 3 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  25. Structured Bayesian Pruning via Log-Normal Multiplicative Noise
    2017/05/20 by Kirill Neklyudov, Dmitry Molchanov, Neklyudov, Kirill +5 · 1 citation
    Computer Science · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML)
  26. Where Do Large Learning Rates Lead Us?
    2024/10/29 by Ildus Sadrtdinov, Sadrtdinov, Ildus, Maxim Kodryan +7 · 4 citations
    Computer Science · #Online Learning and Analytics
  27. Variance Networks: When Expectation Does Not Meet Your Expectations
    2018/03/10 by Kirill Neklyudov, Neklyudov, Kirill, Dmitry Molchanov +5 · 1 citation
    Computer Science · Physics and Astronomy · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  28. Importance Weighted Hierarchical Variational Inference
    2019/05/08 by Artem Vladimirovich Sobolev, Dmitry Vetrov, Sobolev, Artem +1 · 1 citation
    Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
  29. Diffusion on language model encodings for protein sequence generation
    2024/03/06 by Viacheslav Meshchaninov, Meshchaninov, Viacheslav, П. В. Страшнов +11 · 2 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Artificial Intelligence (cs.AI) #Biomedical Text Mining and Ontologies #Biomolecules (q-bio.BM) #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Topic Modeling
  30. Stochasticity in Neural ODEs: An Empirical Study
    2020/02/22 by Oganesyan, Viktor, Volokhova, Alexandra, Vetrov, Dmitry · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  31. Involutive MCMC: a Unifying Framework
    2020/06/30 by Neklyudov, Kirill, Welling, Max, Egorov, Evgenii +1 · 1 citation
    #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
  32. Deterministic Decoding for Discrete Data in Variational Autoencoders
    2020/03/04 by Polykovskiy, Daniil, Vetrov, Dmitry · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  33. Towards Practical Credit Assignment for Deep Reinforcement Learning
    2021/06/08 by Alipov, Vyacheslav, Simmons-Edler, Riley, Putintsev, Nikita +2 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  34. Quantization of Generative Adversarial Networks for Efficient Inference: a Methodological Study
    2021/08/31 by Andreev, Pavel, Fritzler, Alexander, Vetrov, Dmitry · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  35. HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach
    2024/04/01 by Maxim Nikolaev, Nikolaev, Maxim, М. В. Кузнецов +5 · 2 citations
    Computer Science · Materials Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Image Enhancement Techniques #Textile materials and evaluations
  36. Automating Control of Overestimation Bias for Reinforcement Learning
    2021/10/26 by Kuznetsov, Arsenii, Grishin, Alexander, Tsypin, Artem +3 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Robotics (cs.RO)
  37. Improving GFlowNets with Monte Carlo Tree Search
    2024/06/19 by Н. Ф. Морозов, Daniil Tiapkin, Morozov, Nikita +7 · 2 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Data Stream Mining Techniques #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications
  38. Submodular Decomposition Framework for Inference in Associative Markov\n Networks with Global Constraints
    2011/03/05 by Anton Osokin, Dmitry Vetrov, Osokin, Anton +3 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Bayesian Modeling and Causal Inference #Computer Vision and Pattern Recognition (cs.CV) #Discrete Mathematics (cs.DM) #FOS: Computer and information sciences #FOS: Mathematics #Gene expression and cancer classification #Graph Theory and Algorithms #Optimization and Control (math.OC)
  39. On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay
    2021/06/29 by Lobacheva, Ekaterina, Kodryan, Maxim, Chirkova, Nadezhda +2 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  40. Gradual Optimization Learning for Conformational Energy Minimization
    2023/11/05 by Artem Tsypin, Leonid Ugadiarov, Tsypin, Artem +17 · 1 citation
    Chemistry · Computer Science · Materials Science · #Chemical Physics (physics.chem-ph) #Computational Drug Discovery Methods #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Various Chemistry Research Topics
  41. Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes
    2022/09/08 by Kodryan, Maxim, Lobacheva, Ekaterina, Nakhodnov, Maksim +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)