References and software

A concise reference for the core Monge-Kantorovich theory, duality, cyclical monotonicity, and regularity themes.

The broad modern reference for Wasserstein geometry, displacement convexity, curvature, and analytical applications.

A very readable route from measure theory and convex analysis to PDE, modeling, and numerical viewpoints.

The standard reference for metric gradient flows, Wasserstein gradient-flow theory, and the JKO viewpoint.

The closest companion to the computational side of OT4ML, especially discrete solvers, Sinkhorn methods, and applications.

Explains the economic and matching-theoretic language behind assignment, duality, surplus, and equilibrium interpretations.

A modern monograph-style treatment of statistical rates, empirical measures, and inference in Wasserstein geometry.

A compact introduction to existence, stability, duality, and the geometric objects used later in Wasserstein spaces.

Background for matrix scaling, Hilbert metric arguments, and the classical convergence theory behind Sinkhorn iterations.

A recent survey focused on computational compromises needed by machine-learning scale problems.

A broad ML-oriented review covering OT losses, regularization, domain adaptation, and learning applications.

The main survey for the path-space Schrödinger problem and its relation to entropic OT.

A pedagogical bridge from Euclidean gradient flows to Wasserstein gradient flows and entropy methods.

A visual and geometric survey of OT methods for color, shape, imaging, and computer-vision problems.