A Role for Message Passing in Data Assimilation?
Speaker: Marc Deisenroth (University College London)
Location: Building 303A Aud. 43, DTU Lyngby Campus
Estimating the latent state of a dynamical system based on noisy observations is a common challenge underlying many tasks in engineering, robotics, or weather modeling. We will discuss two perspectives of state estimation: temporal inference and spatial inference. In this talk, I will provide a machine learning perspective on state estimation and discuss what role message passing can play when solving large-scale spatio-temporal inference problems as they appear in data assimilation.