Machine Learning for Physicists (Lecture 9): Boltzmann machines

Lecture 9: Boltzmann machines Contents: Boltzmann machines as a way to generate samples from an observed probability distribution (e.g. images that look like images that have been observed), connection to statistical physics and Monte Carlo sampling, applications in physics Lecture series by Florian Marquardt: Introduction to deep learning for physicists. The whole series covers: Backpropagation, convolutional networks, autoencoders, recurrent networks, Boltzmann machines, reinforcement learning, and more. Lectures recorded in 2019, tutorials delivered in 2020 online. Friedrich-Alexander Universität Erlangen-Nürnberg, Germany (). This video on the official FAU channel: