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Continual Learning of Dynamical Systems in Recurrent Neural Networks through Recyclable Unit Gating

Dynamical Systems Reconstruction (DSR) aims to infer models from observed time series that reproduce a system's qualitative long-term behavior. Continual DSR (cDSR) requires learning new systems while preserving previously learned dynamics, yet even small parameter updates in recurrent models can…

By Sima Hashemi, Daniel Durstewitz, Georgia KoppearXiv cs.LG

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Originally published by arXiv cs.LG on Oct 1, 2026.

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