Tensor Networks for Machine Learning and Applications
Institute for Pure & Applied Mathematics (IPAM) via YouTube
Overview
Syllabus
Introduction
Quantitization
Models
Whats Appealing
Benefits
Notation
Tensor Train
Quantum Physics
General Power Tools
Machine Learning
Infinite Matrix Product States
Locally Purified States
Projected entangled pair states
Fixed mirror layers
Why should tensor networks work
Mutual information of image data
Algorithms
Local update
Density matrix
Applications
Downsides
Taught by
Institute for Pure & Applied Mathematics (IPAM)