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.
- 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
- [Updated 12.09]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
- [Updated 30.08]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 (Community Day (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
- [Updated 04.09]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