Variational and Information Flows in Machine Learning and Optimal Transport

“This book is a collection of four short monographs exploring the theoretical foundations of optimal transport and its connections with machine learning. Each part can be read independently, but together they form a coherent and well-structured overview of the field. I would recommend this volume both as an accessible entry point for researchers with a strong theoretical background wishing to explore applications in machine learning, and as a rigorous theoretical reference for graduate students in data science or applied mathematics.” (Ronan Herry, zbMATH 1576.49001, 2026)