2026
Information dynamics and Memory in Neural Networks through Fisher Information Diffusion
ICML 2026spotlight
We present a general theoretical framework for analyzing how information about past inputs is encoded in recurrent networks into evolving dynamics rather than being represented as convergence to static attractors. Using dynamic mean-field theory and diffusion from physics, we derive a Fisher informa…