Michael Figurnov
Michael Figurnov
DeepMind
Verified email at google.com
Title
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Cited by
Year
Spatially adaptive computation time for residual networks
M Figurnov, MD Collins, Y Zhu, L Zhang, J Huang, D Vetrov, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
1212017
Perforatedcnns: Acceleration through elimination of redundant convolutions
M Figurnov, A Ibraimova, DP Vetrov, P Kohli
Advances in Neural Information Processing Systems, 947-955, 2016
922016
Implicit reparameterization gradients
M Figurnov, S Mohamed, A Mnih
Advances in Neural Information Processing Systems, 441-452, 2018
632018
Monte carlo gradient estimation in machine learning
S Mohamed, M Rosca, M Figurnov, A Mnih
arXiv preprint arXiv:1906.10652, 2019
262019
Variational autoencoder with arbitrary conditioning
O Ivanov, M Figurnov, D Vetrov
arXiv preprint arXiv:1806.02382, 2018
202018
Tensor train decomposition on tensorflow (t3f)
A Novikov, P Izmailov, V Khrulkov, M Figurnov, I Oseledets
Journal of Machine Learning Research 21 (30), 1-7, 2020
82020
Probabilistic adaptive computation time
M Figurnov, A Sobolev, D Vetrov
arXiv preprint arXiv:1712.00386, 2017
52017
Linear combination of random forests for the Relevance Prediction Challenge
M Figurnov, A Kirillov
Proc. of Int. Conf. on Web Service and Data Mining workshop on Web Search …, 2012
52012
Robust variational inference
M Figurnov, K Struminsky, D Vetrov
arXiv preprint arXiv:1611.09226, 2016
22016
Устойчивый к шуму метод обучения вариационного автокодировщика
МВ Фигурнов, КА Струминский, ДП Ветров
Интеллектуальные системы. Теория и приложения 21 (2), 90-109, 2017
12017
Entropy Estimates for Generative Models
K Struminsky, M Figurnov, D Vetrov
2018
Universal Conditional Machine.
O Ivanov, M Figurnov, DP Vetrov
CoRR, 2018
2018
Measure-Valued Derivatives for Approximate Bayesian Inference
M Rosca, M Figurnov, S Mohamed, A Mnih
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Articles 1–13