Summary
This course covers the statistical physics approach to computer science problems ranging from graph theory and constraint satisfaction to inference and machine learning. In particular the replica and cavity methods, message passings algorithms, and analysis of the related phase transitions.
Lecture notes : Written lecture notes are here: Chapter 1-13
Please do not hesitate to report mistakes, typos, inconsistencies, clarity issues. These notes will be also used for reference, and for the exercices.
Videos : Videos of the course will be posted on the channel in switchtube
- Professor: Vittorio Erba
- Professor: Florent Krzakala
- Professor: Lenka Zdeborová
- Teacher: Hugo Chao Cui
- Teacher: Yatin Dandi
- Teacher: Emanuele Troiani
