Bridging Control, Inference, Transport, and Thermodynamics: From Theory to Applications in Learning

The last decade has seen the development of powerful methods for learning complex structure from high-dimensional data. These advances have brought to the foreground fundamental connections between subdisciplines of physics, applied mathematics, and machine learning. In this review, we bring togethe