- Research Fellow:Faculty of Computer Science / Big Data and Information Retrieval School / International Laboratory of Deep Learning and Bayesian Methods
- Michael Figurnov has been at HSE since 2015.
Research on acceleration of convolutional neural networks and neural Bayesian methods.
Diploma in Applied Mathematics and Information Science
Lomonosov Moscow State University
Continuing education / Professional retraining / Internships / Study abroad experience
2016 - Google Seattle, USA, intern, supervisor: Li Zhang
2015 - University of Toronto, Canada, visiting student, supervisor: Ruslan Salakhutdinov
- Chapter Figurnov M., Collins M. D., Zhu Y., Zhang L., Huang J., Vetrov D., Salakhutdinov R. Spatially Adaptive Computation Time for Residual Networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017). Curran Associates, Inc., 2017. P. 1039-1048.
- Article Фигурнов М. В., Струминский К. А., Ветров Д. П. Устойчивый к шуму метод обучения вариационного автокодировщика // Интеллектуальные системы. Теория и приложения. 2017. Т. 21. № 2. С. 90-109.
- Chapter Figurnov M., Ibraimova A., Vetrov D., Kohli P. PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions, in: Advances in Neural Information Processing Systems 29 (NIPS 2016). NY : Curran Associates, 2016.
- Preprint Figurnov M., Collins M. D., Zhu Y., Zhang L., Huang J., Vetrov D., Salakhutdinov R. Spatially Adaptive Computation Time for Residual Networks / Cornell University. Series arXiv "arXiv:1612.02297". 2016.
Michael Fugurnov's paper written in collaboration with researchers from Google, Carnegie Mellon University and Dmitry Vetrov has been presented on Computer Vision and Pattern Recognition. The conference was held from 21 to 26 July in Honolulu, USA.
On June 9, a summit was held on computer vision and deep learning ‘Machines can see’, organized by Sistema VC, Visionlabs, and the Strelka Institute. Dmitry Vetrov and Anton Konushin, staff members of HSE Faculty of Computer Science, were among the organizers of and speakers at the conference.
In December 2016, five new international laboratories opened up at the Higher School of Economics, one of which was the International Laboratory of Deep Learning and Bayesian Methods. This lab focuses on combined neural Bayesian models that bring together two of the most successful paradigms in modern-day machine learning – the neural network paradigm and the Bayesian paradigm.
Interdisciplinary Seminar of the Strategic Academic Unit 'Mathematics, Computer Science, and Information Technology'
A regular research seminar aimed at sharing the results of research conducted as part of of the Strategic Academic Unit ‘Mathematics, Computer Science, and Information Technology’ and determining prospective interdisciplinary fields was recently held at HSE. This seminar will be organized regularly by different departments within the Strategic Academic Unit.