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  2. PHYSICS 265

Statistical Mechanics of Spin Glasses and Neural Networks
PHYSICS 265

Course Information

Description

The course will survey advanced statistical physics approaches in the study of complex natural and artificial systems, spanning theory of spin glasses, random matrices, random dynamical systems, random graphs, and neural networks, with applications to the physics of spin glasses, chaos in random circuits, memory and learning in recurrent and deep neural networks. Surveyed methods include Replica Theory, Dynamic Mean Fields, Cavity and Message Passing, Kernels and Gaussian Processes.

School Faculty of Arts & Sciences
Credits 4
Cross Reg

Available for Harvard Cross Registration

Department Physics
Course Component Lecture
Subject Physics
Grading Basis FAS Letter Graded
General Education N/A
Quantitative Reasoning with Data N/A
Divisional Distribution Science & Engineering & Applied Science
Course Level Primarily for Graduate Students