Recorded 21 May 2025. Tyler Maunu of Brandeis University presents "Subspace Langevin Monte Carlo" at IPAM's Statistical and Numerical Methods for Non-commutative Optimal Transport Workshop. Abstract: Sampling from high-dimensional distributions poses significant computational challenges. We introduce Subspace Langevin Monte Carlo (SLMC), a novel and efficient sampling method that generalizes coordinate and preconditioned Langevin Monte Carlo. At a higher level, our method can be viewed as a natural extension of subspace descent techniques from Euclidean space to Wasserstein space. If time permits, we will discuss subspace Wasserstein descent in other settings. Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-iii-statistical-and-numerical-methods-for-non-commutative-optimal-transport/