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Regular version of the site

Educational activity

Over the years Bayesian methods research group, on the basis of which a laboratory was established, collected expertise in the field of Bayesian methods, deep learning and optimization techniques. This knowledge formed the basis of several training courses and allow the laboratory staff to explain material in clear language to students. The courses follow proven format that involves active work of students during the semester and aims at students ' understanding of the subject, not the memorization of basic facts. 

Courses taught by laboratory staff:

  1. Optimization methods
  2. Machine learning 1
  3. Research seminar "Machine learning and applications"
  4. Introduction to data analysis (course for minor)
  5. Bayesian methods for machine learning (fall 2017)
Laboratory scientists manage projects of undergraduate students. D. Vetrov is a scientific advisor of several Ph. D. students. Novi Quadranto is expected to manage master's and Ph. D. dissertations.

The laboratory organizes its research activities. In 2017 we are going to invite foreign lecturers and hold Summer School on Bayesian methods in deep learning.

 

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