Soumik Pal - On the Mirror Langevin Diffusions скачать в хорошем качестве

Soumik Pal - On the Mirror Langevin Diffusions

This lecture was part of the Workshop on "Probabilistic Mass Transport - from Schrödinger to Stochastic Analysis" held at the ESI February 9 - 13, 2026. The Mirror Langevin Diffusions, first introduced in the context of machine learning in 2020/21, is a new entrant in the classical families of diffusions. It was soon realized that these are Langevin diffusions on Hessian manifolds, and just like the Euclidean Langevin diffusions these are fundamental. I will give an overview of this family and how it relates to Wasserstein gradient flows, Schrödinger bridges, Sinkhorn algorithms, sampling techniques and many other topics of recent interest. Many of the key properties of this family of diffusions are yet to be discovered.