Monthly Archives: June 2020

Criticality in deep neural nets

Posted on June 19, 2020 by rojefferson

In the previous post, we introduced mean field theory (MFT) as a means of approximating the partition function for interacting systems. In particular, we used this to determine the critical point at which the system undergoes a phase transition, and … Continue reading →

Posted in Minds & Machines | 2 Comments

Mean field theory: from physics to deep neural nets

Posted on June 13, 2020 by rojefferson

In a previous post, I alluded to the question of whether criticality played any role in deep neural networks. The question I originally had in mind was whether the fact that the correlation length diverges at a critical point implies … Continue reading →

Posted in Physics | Leave a comment