Adaptive Deep Neural Network Approximation for Stochastic Dynamical Systems

This paper proposes a new adaptive deep learning method called temporal KRnet (tKRnet) to efficiently approximate the probability density functions (PDFs) of state variables in stochastic dynamical systems governed by the Liouville equation.