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Nikita Kotelevskii
Nikita Kotelevskii
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
Verified email at mbzuai.ac.ae
Title
Cited by
Cited by
Year
Monte Carlo variational auto-encoders
A Thin, N Kotelevskii, A Doucet, A Durmus, E Moulines, M Panov
International Conference on Machine Learning, 10247-10257, 2021
612021
Fedpop: A bayesian approach for personalised federated learning
N Kotelevskii, M Vono, A Durmus, E Moulines
Advances in Neural Information Processing Systems 35, 8687-8701, 2022
582022
Nonparametric uncertainty quantification for single deterministic neural network
N Kotelevskii, A Artemenkov, K Fedyanin, F Noskov, A Fishkov, ...
Advances in Neural Information Processing Systems 35, 36308-36323, 2022
49*2022
Predictive uncertainty quantification via risk decompositions for strictly proper scoring rules
N Kotelevskii, M Panov
CoRR, 2024
23*2024
MetFlow: a new efficient method for bridging the gap between Markov chain Monte Carlo and variational inference
A Thin, N Kotelevskii, JS Denain, L Grinsztajn, A Durmus, M Panov, ...
arXiv preprint arXiv:2002.12253, 2020
202020
Efficient conformal prediction under data heterogeneity
V Plassier, N Kotelevskii, A Rubashevskii, F Noskov, M Velikanov, ...
International Conference on Artificial Intelligence and Statistics, 4879-4887, 2024
132024
Dirichlet-based uncertainty quantification for personalized federated learning with improved posterior networks
N Kotelevskii, S Horváth, K Nandakumar, M Takáč, M Panov
arXiv preprint arXiv:2312.11230, 2023
122023
Nonreversible MCMC from conditional invertible transforms: a complete recipe with convergence guarantees
A Thin, N Kotelevskii, C Andrieu, A Durmus, E Moulines, M Panov
arXiv preprint arXiv:2012.15550, 2020
102020
Learning confident classifiers in the presence of label noise
AA Hashmi, A Zhumabayeva, N Kotelevskii, A Agafonov, M Yaqub, ...
Proceedings of the 2025 SIAM International Conference on Data Mining (SDM …, 2025
42025
Metropolized flow: from invertible flow to mcmc
A Thin, N Kotelevskii, A Durmus, M Panov, E Moulines
Proceedings of the ICML Workshop on Invertible Neural Networks, Normalizing …, 2020
32020
Adaptive Temperature Scaling with Conformal Prediction
N Kotelevskii, M Guizani, E Moulines, M Panov
arXiv preprint arXiv:2505.15437, 2025
22025
Method and system for determining uncertainty in personalized federated learning
M PANOV, N KOTELEVSKII, M Takac, S HORVATH
US Patent App. 18/738,622, 2025
2025
Uncertainty Quantification for Regression using Proper Scoring Rules
A Fishkov, K Schweighofer, M Ielanskyi, N Kotelevskii, M Guizani, ...
arXiv preprint arXiv:2509.26610, 2025
2025
Neural Optimal Transport Meets Multivariate Conformal Prediction
V Kondratyev, A Fishkov, N Kotelevskii, M Hegazy, R Flamary, M Panov, ...
arXiv preprint arXiv:2509.25444, 2025
2025
Multidimensional Uncertainty Quantification via Optimal Transport
N Kotelevskii, M Goloburda, V Kondratyev, A Fishkov, M Guizani, ...
arXiv preprint arXiv:2509.22380, 2025
2025
Who to Trust? Aggregating Client Knowledge in Logit-Based Federated Learning
V Kovalchuk, N Kotelevskii, M Panov, S Horváth, M Takáč
arXiv preprint arXiv:2509.15147, 2025
2025
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