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Regular version of the site

Centre of Deep Learning and Bayesian Methods

2

April 19

Part of the Centre of Deep Learning and Bayesian Methods and another partner project between Sberbank and HSE University’s Faculty of Computer Science, the laboratory will focus on applying machine learning methods to financial services.

January 06

One paper will be presented at AISTATS (Japan, April 2019) and three papers will be presented at ICLR (USA, May 2019).
Publications
Article
Semi-Conditional Normalizing Flows for Semi-Supervised Learning

Atanov A., Volokhova A., Ashukha A. et al.

Working papers by Cornell University. Series math "arxiv.org". 2019.

Book chapter
Conditional Generators of Words Definitions

Gadetsky A., Yakubovskiy I., Vetrov D.

In bk.: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics. Vol. 2: Short Papers. Association for Computational Linguistics, 2018. P. 266-271.

Working paper
Variational Dropout via Empirical Bayes

Kharitonov V., Molchanov D., Vetrov D.

stat.ML. arxiv.org. Cornell University, 2018

About the Center

International Laboratory of Deep Learning and Bayesian Methods is established on the basis of Bayesian Methods Research Group. The group is one of the strongest scientific groups in Russia in the area of machine learning and probabilistic modeling. The laboratory researches the neurobayesian models that combine the advantages of the two most successful machine learning approaches, namely neural networks and Bayesian methods.