Paper ID: 2410.10523

Inverse Problems and Data Assimilation: A Machine Learning Approach

Eviatar Bach, Ricardo Baptista, Daniel Sanz-Alonso, Andrew Stuart

The aim of these notes is to demonstrate the potential for ideas in machine learning to impact on the fields of inverse problems and data assimilation. The perspective is one that is primarily aimed at researchers from inverse problems and/or data assimilation who wish to see a mathematical presentation of machine learning as it pertains to their fields. As a by-product, we include a succinct mathematical treatment of various topics in machine learning.

Submitted: Oct 14, 2024