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Regular version of the site

Centre of Deep Learning and Bayesian Methods

Publications
Article
A randomized coordinate descent method with volume sampling

Rodomanov A., Kropotov D.

SIAM Journal on Optimization. 2020. Vol. 30. No. 3. P. 1878-1904.

Book chapter
Variational Autoencoder with Arbitrary Conditioning

Vetrov D., Ivanov O.

In bk.: Proceedings of the 7th International Conference on Learning Representations (ICLR 2019). ICLR, 2019. P. 1-25.

Working paper
Low-variance Gradient Estimates for the Plackett-Luce Distribution

Gadetsky A., Struminsky K., Robinson C. et al.

Bayesian Deep Learning NeurIPS 2019 Workshop. 2019. Bayesian Deep Learning NeurIPS 2019 Workshop, 2019

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.