Jointly Learning Dynamics and Data Assimilation from Sparse Observations using End-to-End Deep Learning

A novel end-to-end deep learning framework, CODA, that jointly learns dynamical models and performs data assimilation directly from sparse and noisy observations, without requiring access to ground truth system states.