Action Matching: Learning Stochastic Dynamics from Samples
Offered By: Generative Memory Lab via YouTube
Course Description
Overview
Explore a comprehensive presentation on the paper "Action Matching: Learning Stochastic Dynamics from Samples" delivered by Kirill Neklyudov. Delve into the innovative approach of learning stochastic dynamics from sample data, gaining insights into the methodology, applications, and implications of this research. Understand the key concepts, challenges, and potential advancements in the field of generative modeling and stochastic processes through this in-depth 94-minute talk from the Generative Memory Lab.
Syllabus
Action Matching: Learning Stochastic Dynamics from Samples
Taught by
Generative Memory Lab
Related Courses
Bayesian Computational StatisticsIllinois Institute of Technology via Coursera Mathematical understanding of uncertainty
Seoul National University via edX Probabilistic Graphical Models 2: Inference
Stanford University via Coursera Mathematical Foundation of Various MCMC Methods
Institut des Hautes Etudes Scientifiques (IHES) via YouTube Wasserstein Gradient Flows and Applications to Sampling in Machine Learning - Lecture 1
Centre International de Rencontres Mathématiques via YouTube