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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 qu
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