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

Centre of Deep Learning and Bayesian Methods

2

July 30

24 of July Alexander Shekhovtsov (Czech Technical University in Prague), invited by the Centre of Deep Learning and Bayesian Methods, and Belhal Karimi (Ecole Polytechnique & INRIA), a summer intern of the Centre, made presentations at the Faculty of Computer Science
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
The Deep Weight Prior

Atanov A., Ashukha A., Struminsky K. et al.

In bk.: Proceedings of the 7th International Conference on Learning Representations (ICLR 2019). 2019.

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.