| Structured bayesian pruning via log-normal multiplicative noise K Neklyudov, D Molchanov, A Ashukha, DP Vetrov Advances in Neural Information Processing Systems 30, 2017 | 207 | 2017 |
| Performance of machine learning algorithms in predicting game outcome from drafts in dota 2 A Semenov, P Romov, S Korolev, D Yashkov, K Neklyudov Analysis of Images, Social Networks and Texts: 5th International Conference …, 2017 | 75 | 2017 |
| Uncertainty estimation via stochastic batch normalization A Atanov, A Ashukha, D Molchanov, K Neklyudov, D Vetrov Advances in Neural Networks–ISNN 2019: 16th International Symposium on …, 2019 | 55 | 2019 |
| Involutive MCMC: a unifying framework K Neklyudov, M Welling, E Egorov, D Vetrov International Conference on Machine Learning, 7273-7282, 2020 | 32 | 2020 |
| Variance networks: When expectation does not meet your expectations K Neklyudov, D Molchanov, A Ashukha, D Vetrov arXiv preprint arXiv:1803.03764, 2018 | 27 | 2018 |
| Metropolis-Hastings view on variational inference and adversarial training K Neklyudov, E Egorov, P Shvechikov, D Vetrov arXiv preprint arXiv:1810.07151, 2018 | 18 | 2018 |
| Applications of Machine Learning in Dota 2: Literature Review and Practical Knowledge Sharing. AM Semenov, P Romov, K Neklyudov, D Yashkov, D Kireev MLSA@ PKDD/ECML, 2016 | 12 | 2016 |
| Orbital mcmc K Neklyudov, M Welling International Conference on Artificial Intelligence and Statistics, 5790-5814, 2022 | 8 | 2022 |
| Action Matching: Learning Stochastic Dynamics from Samples K Neklyudov, R Brekelmans, D Severo, A Makhzani | 6* | 2023 |
| Deterministic gibbs sampling via ordinary differential equations K Neklyudov, R Bondesan, M Welling arXiv preprint arXiv:2106.10188, 2021 | 4 | 2021 |
| The Implicit Metropolis-Hastings Algorithm K Neklyudov, E Egorov, D Vetrov Advances in Neural Information Processing Systems, 2019, 2019 | 4 | 2019 |
| Maxentropy pursuit variational inference E Egorov, K Neklydov, R Kostoev, E Burnaev Advances in Neural Networks–ISNN 2019: 16th International Symposium on …, 2019 | 3 | 2019 |
| Quantum hypernetworks: Training binary neural networks in quantum superposition J Carrasquilla, M Hibat-Allah, E Inack, A Makhzani, K Neklyudov, ... arXiv preprint arXiv:2301.08292, 2023 | 1 | 2023 |
| Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schr\" odinger Equation K Neklyudov, J Nys, L Thiede, J Carrasquilla, Q Liu, M Welling, ... arXiv preprint arXiv:2307.07050, 2023 | | 2023 |
| Particle Dynamics for Learning EBMs K Neklyudov, P Jaini, M Welling arXiv preprint arXiv:2111.13772, 2021 | | 2021 |
Dmitry VetrovHigher School of Economics, AI Research Institute, MoscowVerified email at hse.ru
