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Behavioral Mapping of Hierarchical Dynamical Models Accelerates Bayesian Parameter Inference
Bayesian parameter inference for complex nonlinear dynamical models is often limited by the cost of repeated model simulation. We present a behavioral mapping framework that uses the inferred posterior of a higher-level model to accelerate inference of a lower-level model without requiring state or
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