Optimal transport is a simple yet powerful mathematical framework for comparing and connecting probability distributions and/or data sets. It is rapidly gaining popularity across a range of fields. This workshop introduces the fundamental concepts in an accessible way and showcases a variety of applications, including machine learning, cognitive science, and computational biology.

Lunch will be provided to all participants.

Participants should have a basic familiarity with probability; matrix/vector operations; logarithms/exponents. No coding experience required.

The format of this workshop is presentation with open Q&A. Python notebooks will be made available after the session.