arXiv:1804.04378
공식 코드 · Papers with Code
Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs
원문 초록
Parameter identification and comparison of dynamical systems is a challenging task in many fields. Bayesian approaches based on Gaussian process regression over time-series data have been successfully applied to infer the parameters of a dynamical system without explicitly solving it. While the benefits in computational cost are well established, a rigorous mathematical framework has been missing. We offer a novel interpretation which leads to a better understanding and improvements in state-of-the-art performance in terms of accuracy for nonlinear dynamical systems.
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