About the Center
The center conducts research at the intersection of two actively developing areas of data analysis: deep learning and Bayesian methods of machine learning methods. Deep learning is a section that involves building very complex models (neural networks) to solve problems such as classifying images or music, transferring an art style from picture to photograph, predicting the next words in a text. Within the framework of the Bayesian approach, probabilistic models based on the apparatus of probability theory and mathematical statistics are considered for solving such problems.
The center was created on the basis of the Bayesian Methods Research Group.