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Event Details Topic This workshop brings together two exciting new directions in research: stochastic transport and Wasserstein projections. Stochastic transport studies how processes evolve over time rather than as instant shifts, making it particularly useful for dynamic systems where decisions depend on the flow of information.

Event Details For full details on this event, please see the corresponding BIRS event page. Description The Banff International Research Station will host the “Wasserstein Gradient Flows in Math and Machine Learning” workshop in Banff from June 29 - July 4, 2025.

Lipschitz transport maps between two measures are useful tools for transferring analytical properties, such as functional inequalities. …

Denoising Diffusion models have revolutionized generative modeling. Conceptually, these methods define a transport mechanism from a …

In this talk, we study a variational problem that provides a way to extend minimizing geodesics connecting two given probability …

In this talk, we will discuss the question of establishing CLTs for empirical entropic optimal transport when choosing the …

Measures provide valuable insights into long-term and global behaviors across a broad range of dynamical systems. In this talk, we …

Gradient flows have emerged as a powerful framework for analyzing machine learning and statistical inference algorithms. Motivated by …