Completed
Albert Cohen: Theory of approximation of hight-dimensional functions - lecture 2
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
CEMRACS 2021 - Mathematical and Computational Methods for High-Dimensional Problems
Automatically move to the next video in the Classroom when playback concludes
- 1 Tony Lelièvre: How to compute transition times?
- 2 Claudia Schillings: Bayesian data assimilation and filtering - lecture 2
- 3 Johannes Schmidt-Hieber: Statistical theory for deep neural networks - lecture 2
- 4 Johannes Schmidt-Hieber: Statistical theory for deep neural networks - lecture 1
- 5 Olivier Lafitte: Coupling models instead of coupling codes: two toy examples
- 6 Anthony Nouy: Approximation and learning with tree tensor networks - Lecture 2
- 7 Anthony Nouy: Approximation and learning with tree tensor networks - Lecture 1
- 8 Albert Cohen: Theory of approximation of hight-dimensional functions - lecture 2
- 9 Massoumeh Dashti: Bayesian methods for inverse problems - lecture 2
