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Kirill Neklyudov
Kirill Neklyudov
Vector Institute
Verified email at vectorinstitute.ai - Homepage
Title
Cited by
Cited by
Year
Structured bayesian pruning via log-normal multiplicative noise
K Neklyudov, D Molchanov, A Ashukha, DP Vetrov
Advances in Neural Information Processing Systems 30, 2017
2172017
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
872017
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
582019
Involutive MCMC: a unifying framework
K Neklyudov, M Welling, E Egorov, D Vetrov
International Conference on Machine Learning, 7273-7282, 2020
362020
Variance networks: When expectation does not meet your expectations
K Neklyudov, D Molchanov, A Ashukha, D Vetrov
arXiv preprint arXiv:1803.03764, 2018
312018
Action Matching: Learning Stochastic Dynamics from Samples
K Neklyudov, R Brekelmans, D Severo, A Makhzani
202023
Metropolis-Hastings view on variational inference and adversarial training
K Neklyudov, E Egorov, P Shvechikov, D Vetrov
arXiv preprint arXiv:1810.07151, 2018
182018
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
132016
Orbital mcmc
K Neklyudov, M Welling
International Conference on Artificial Intelligence and Statistics, 5790-5814, 2022
92022
Deterministic gibbs sampling via ordinary differential equations
K Neklyudov, R Bondesan, M Welling
arXiv preprint arXiv:2106.10188, 2021
62021
Wasserstein quantum Monte Carlo: a novel approach for solving the quantum many-body Schrödinger equation
K Neklyudov, J Nys, L Thiede, J Carrasquilla, Q Liu, M Welling, ...
Advances in Neural Information Processing Systems 36, 2024
42024
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
42023
The Implicit Metropolis-Hastings Algorithm
K Neklyudov, E Egorov, D Vetrov
Advances in Neural Information Processing Systems, 2019, 2019
42019
A computational framework for solving Wasserstein Lagrangian flows
K Neklyudov, R Brekelmans, A Tong, L Atanackovic, Q Liu, A Makhzani
arXiv preprint arXiv:2310.10649, 2023
22023
Maxentropy pursuit variational inference
E Egorov, K Neklydov, R Kostoev, E Burnaev
Advances in Neural Networks–ISNN 2019: 16th International Symposium on …, 2019
22019
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
L Kong, Y Du, W Mu, K Neklyudov, V De Bortol, H Wang, D Wu, A Ferber, ...
arXiv preprint arXiv:2402.18012, 2024
12024
On Schrödinger Bridge Matching and Expectation Maximization
R Brekelmans, K Neklyudov
NeurIPS 2023 Workshop Optimal Transport and Machine Learning, 2023
2023
Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC for Large Neural Nets
W Lin, F Dangel, R Eschenhagen, K Neklyudov, A Kristiadi, RE Turner, ...
arXiv preprint arXiv:2312.05705, 2023
2023
Particle Dynamics for Learning EBMs
K Neklyudov, P Jaini, M Welling
arXiv preprint arXiv:2111.13772, 2021
2021
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