Proposes feature splitting and a closed-form bound on extrapolation range to enable zero-shot topological out-of-domain generalization in dynamical systems reconstruction across tipping points.
A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements.PLoS Comput
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Topological Out-of-Domain Generalization in Dynamical Systems Reconstruction
Proposes feature splitting and a closed-form bound on extrapolation range to enable zero-shot topological out-of-domain generalization in dynamical systems reconstruction across tipping points.