Kirill Struminsky
Kirill Struminsky
НИУ-ВШЭ, Факультет компьютерных наук, Департамент больших данных и информационного поиска
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The deep weight prior. modeling a prior distribution for cnns using generative models
A Atanov, A Ashukha, K Struminsky, D Vetrov, M Welling
arXiv preprint arXiv:1810.06943, 2018
A new approach for sparse Bayesian channel estimation in SCMA uplink systems
K Struminsky, S Kruglik, D Vetrov, I Oseledets
2016 8th International Conference on Wireless Communications & Signal …, 2016
Low-variance black-box gradient estimates for the plackett-luce distribution
A Gadetsky, K Struminsky, C Robinson, N Quadrianto, D Vetrov
Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 10126 …, 2020
Leveraging recursive gumbel-max trick for approximate inference in combinatorial spaces
K Struminsky, A Gadetsky, D Rakitin, D Karpushkin, DP Vetrov
Advances in Neural Information Processing Systems 34, 10999-11011, 2021
Well log data standardization, imputation and anomaly detection using hidden Markov models
K Struminskiy, A Klenitskiy, A Reshytko, D Egorov, A Shchepetnov, ...
Petroleum Geostatistics 2019 2019 (1), 1-5, 2019
Quantifying learning guarantees for convex but inconsistent surrogates
K Struminsky, S Lacoste-Julien, A Osokin
Advances in Neural Information Processing Systems 31, 2018
Differentiable rendering with reparameterized volume sampling
N Morozov, D Rakitin, O Desheulin, D Vetrov, K Struminsky
arXiv preprint arXiv:2302.10970, 2023
Устойчивый к шуму метод обучения вариационного автокодировщика
МВ Фигурнов, КА Струминский, ДП Ветров
Robust variational inference
M Figurnov, K Struminsky, D Vetrov
arXiv preprint arXiv:1611.09226, 2016
A Simple Method to Evaluate Support Size and Non-uniformity of a Decoder-Based Generative Model
K Struminsky, D Vetrov
Analysis of Images, Social Networks and Texts: 8th International Conference …, 2019
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