Learning-Induced Dynamical Transition in Recurrent Neural Networks
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arXiv:2609.19288v1 Announce Type: new Abstract: Learning in recurrent neural networks can fundamentally reshape their underlying dynamics, transforming initially chaotic activity into stable task-dependent behavior. We develop a non-equilibrium dynamical mean-field theory(DMFT) to describe this tra…
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- 2026-09-18 04:00 · arXiv cs.LG
Learning-Induced Dynamical Transition in Recurrent Neural Networks