Normalizing Kalman Filters for Multivariate Time Series Analysis Emmanuel de Bézenac

This paper tackles the modelling of large, complex and multivariate time series panels in a probabilistic setting. To this extent, we present a novel approach reconciling classical state space models with deep learning methods.