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cs.LG2020
Probabilistic solution of chaotic dynamical system inverse problems using Bayesian Artificial Neural Networks
David K. E. Green, Filip Rindler
This paper demonstrates the application of Bayesian Artificial Neural Networks to Ordinary Differential Equation (ODE) inverse problems. We consider the case of estimating an unkno…
cs.LG2019
Model inference for Ordinary Differential Equations by parametric polynomial kernel regression
David K. E. Green, Filip Rindler
Model inference for dynamical systems aims to estimate the future behaviour of a system from observations. Purely model-free statistical methods, such as Artificial Neural Networks…