Paper ID: 2305.02334

Structures of Neural Network Effective Theories

Ian Banta, Tianji Cai, Nathaniel Craig, Zhengkang Zhang

We develop a diagrammatic approach to effective field theories (EFTs) corresponding to deep neural networks at initialization, which dramatically simplifies computations of finite-width corrections to neuron statistics. The structures of EFT calculations make it transparent that a single condition governs criticality of all connected correlators of neuron preactivations. Understanding of such EFTs may facilitate progress in both deep learning and field theory simulations.

Submitted: May 3, 2023