Posts by Collection




MaxEntropy Pursuit Variational Inference


I presented our (Evgenii Egorov, Kirill Neklydov, Ruslan Kostoev and Evgeny Burnaev) work on greedy semi-parametric Variational Inference. We propose a version of the Frank-Wolfe algorithm with entropy regularization in the density space. There are slides and full-text on arXiv, as well as published version.

Implicit Metropolis-Hastings


We have the meeting between “Machine Learning”-people and Physicists at the wonderful workshop Physics inspired Machine Learning. I presented our (Kirill Neklyudov, Evgenii Egorov, Dmitry Vetrov) paper on the fusion between MCMC and GANs. There is a video (in Russian) and very long slides. If you would like to take the global idea instantly, I propose to see our NeurIPS poster.


Bayesian Machine Learning, HSE

Under-graduate course, HSE, Computer Science, 2020

I deliver practical seminars on bayesian machine learning which are complemen- tary to the lectures of Prof. Vetrov. You can find all materials in this repo.

[Deep] Bayesian Machine Learning

Graduate course, Skoltech, CDISE, 9999

I developed materials on Bayesian Machine during autumns in 2018, 2019, 2020. Please visit the following repo. The content is a mixture of the essential introduction, with attention to the exponential families and modern methods for deep learning.