The problem of uncovering different dynamical regimes is of pivotal importance in time series analysis. Switching dynamical systems provide a solution for modeling physical phenomena whose time series data exhibit different dynamical modes. In this work we propose a novel variational RNN model for switching dynamics allowing for both non-Markovian and non-linear dynamical behavior between and within dynamic modes. Attention mechanisms are provided to inform the switching distribution.
Switching Dynamical Systems with Deep Neural Networks
Switching Dynamical Systems with Deep Neural Networks.