Variational inference formulation for a model-free simulation of a dynamical system with unknown parameters by a recurrent neural network

no code implementations • 2 Mar 2020 • Kyongmin Yeo, Dylan E. C. Grullon, Fan-Keng Sun, Duane S. Boning, Jayant R. Kalagnanam

Unlike the classical variational inference, where a factorized distribution is used to approximate the posterior, we employ a feedforward neural network supplemented by an encoder recurrent neural network to develop a more flexible probabilistic model.

Time Series Time Series Analysis +1