Scientific Discovery of Dynamic Hidden States and Differential Law Equations

摘要

This paper proposes a novel approach to discover dynamic hidden states and simultaneous time differential law equations from time series data observed in an objective process. This task has not been addressed in the past work though it is essentially important in scientific discovery since any behaviors of objective processes emerge in time evolution. The promising performance of the proposed approach is demonstrated through the analysis of synthetic data.