Heavy-tailed update distributions arise from information-driven self-organization in nonequilibrium learning

Proceedings of the National Academy of Sciences, volume 122, number 51, December 2025.
ImportanceArtificial neural networks can adapt to tasks while freely exploring possible solutions, in the same way that humans balance curiosity with goal-directed behavior. We show that during training, such networks naturally operate near a critical state. …