lectures

This is the official repository for Machine Learning Summer School 2019, which is taking place at Skoltech Institute of Science and Technology, Moscow, from 26.08 - 06.09.

This repository will contain all of the materials of MLSS lectures.

The list of the current lectures published (will be updated with time):

• Marco Cuturi - Optimal Transport (DAY-1 (26.08), DAY-2 (27.08)): https://github.com/mlss-skoltech/lectures/tree/master/optimal_transport
• Justin Solomon - Geometric Techniques in ML (DAY-1 (26.08), DAY-2 (27.08), DAY-3 (28.09)): https://github.com/mlss-skoltech/lectures/tree/master/geometric_techniques_in_ML
• Matus Jan Telgarsky - Deep Learning Theory (DAY-2 (27.08), DAY-3 (28.08)): https://github.com/mlss-skoltech/lectures/tree/master/deep_learning_theory
• [<b>Updated 12.09</b>]Arthur Gretton - Kernels (DAY-3 (28.08), DAY-4 (29.08), DAY-5 (30.08)): https://github.com/mlss-skoltech/lectures/tree/master/kernels
• Michael Bronstein - Graph Neural Networks (DAY-2 (27.08), DAY-3 (28.09)): https://github.com/mlss-skoltech/lectures/tree/master/graph_neural_networks
• Yarin Gal - Bayesian Deep Learning (DAY-3 (27.08), DAY-4 (28.08)): https://github.com/mlss-skoltech/lectures/tree/master/bayesian_deep_learning
• [<b>Updated 30.08</b>]Joris Mooij - Causality (DAY-4 (29.08)): https://github.com/mlss-skoltech/lectures/tree/master/causality
• Nicolò Cesa-Bianchi - Online Learning (DAY-4 (29.08), DAY-5 (30.08)): https://github.com/mlss-skoltech/lectures/tree/master/online_learning
• William Clements - Reinforcement Learning and Quantum Computing (<b>Community Day</b> (31.08)): https://github.com/mlss-skoltech/lectures/tree/master/COMMUNITY_DAY_RL_in_Quantum_Computing
• Michel Besserve - ML and Neuroscience (DAY-6 (02.09), DAY-7 (03.09)): https://github.com/mlss-skoltech/lectures/tree/master/ml_and_neuroscience
• Isabel Valera - Fairness & Interpretability (DAY-6 (02.09), DAY-7 (03.09)): https://github.com/mlss-skoltech/lectures/tree/master/fairness_interpretability
• [<b>Updated 04.09</b>]Shimon Whiteson - Reinforcement Learning (DAY-6 (02.09), DAY-7 (03.09), DAY-8 (04.09)): https://github.com/mlss-skoltech/lectures/tree/master/reinforcement_learning
• Ulrich Bauer - Topological Data Analysis (DAY-8 (04.09), DAY-9 (05.09)): https://github.com/mlss-skoltech/lectures/tree/master/topological_data_analysis
• Mark Girolami - Probabilistic Numerics (DAY-8 (04.09), DAY-9 (05.09), DAY-10 (06.09)): https://github.com/mlss-skoltech/lectures/tree/master/probabilistic_numerics
• François Bachoc - Advances in Gaussian Process (DAY-9(05.09), DAY-10 (06.09)): https://github.com/mlss-skoltech/lectures/tree/master/gaussian_processes
• Evgeny Burnaev - Deep Bayesian Generative Models for Knowledge Transfer and MRI Processing (DAY-10 (06.09)): https://github.com/mlss-skoltech/lectures/tree/master/deep_bayesian_generative_models%20