• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Centre of Deep Learning and Bayesian Methods

2

September 11

The second Summer School on Deep Learning and Bayesian Methods was held in Moscow from August 27 to September 1, this year in English. During 6 days participants were studying and implementing Bayesian methods in neural networks, exchanging their experience and discussing research ideas. 

March 05

Samsung-HSE Laboratory will develop mechanisms of Bayesian inference in modern neural networks, which will solve a number of problems in deep learning. The laboratory team will be made up of the members of the Bayesian Methods Research Group — one of the strongest scientific groups in Russia in the field of machine learning and Bayesian inference. It will be headed by a professor of the Higher School of Economics Dmitry Vetrov.
Publications
Article
Tree-Serial Parametric Dynamic Programming With Flexible Prior Model For Image Denoising
In print

Pham Cong T., Копылов А.

Computer Optics. 2018. P. 1-8.

Book chapter
Bayesian Compression for Natural Language Processing

Chirkova N., Lobacheva E., Vetrov D.

In bk.: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2018.

Working paper
Monotonic models for real-time dynamic malware detection

Chistyakov A., Lobacheva E., Shevelev A. et al.

Workshop of the 6th International Conference on Learning Representations (ICLR). 1. International Conference on Learning Representations, 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.