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A Lyapunov Condition for Training ODEs

2021-09-27 · NeurIPS Workshop DLDE 2021 12 · Anonymous

Control theory is widely used in the study of differential equations to obtain desired behavior from underlying dynamics. We propose a novel method for training ordinary differential equations by using a control-theoretic Lyapunov Condition for stability. This method avoids rolling-out ODE's during training and thus saves the cost of back propagating through a solver or using the adjoint method. We validate our approach experimentally and verify that it has similar performance to ODEs trained by backpropagating through rollouts.

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