A Bayesian sparse identification framework using model averaging recovers interaction structures in dynamical systems with quantified uncertainty in term inclusion.
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In finite-size adaptive networks with delays, heterogeneous nucleation produces single-step or multi-step synchronization transitions controlled by delay magnitude and frequency distribution class, with an analytical upper bound for two-cluster states.
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Uncertainty-Aware Sparse Identification of Dynamical Systems via Bayesian Model Averaging
A Bayesian sparse identification framework using model averaging recovers interaction structures in dynamical systems with quantified uncertainty in term inclusion.
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Delay-Controlled Heterogeneous Nucleation in Adaptive Dynamical Networks
In finite-size adaptive networks with delays, heterogeneous nucleation produces single-step or multi-step synchronization transitions controlled by delay magnitude and frequency distribution class, with an analytical upper bound for two-cluster states.