Pacific Interdisciplinary hub on Optimal Transport

2021 2024

The Pacific Interdisciplinary hub on Optimal Transport (PIHOT) is a Collaborative Research Group examining the research and applications of Optimal Transportation across a wide audience of researchers, students, industry, policy makers and the general public. 

 

The Kantorovich Initiative is a dedicated website to help foster a community around the topic of Optimal Transportation.

Scientific, Seminar
PIHOT CRG Seminar: Guillaume Carlier
June 5, 2021
Online
Entropic optimal transport has received a lot of attention in recent years and has become a popular framework for computational optimal transport thanks to the Sinkhorn scaling algorithm. In this talk, I will discuss the multi-marginal case which...
Scientific, Seminar
PIHOT CRG Seminar: Jan-Christian Hutter
September 30, 2021
Online
The theory of optimal transport (OT) gives rise to distance measures between probability distributions that take the geometry of the underlying space into account. OT is often used in the analysis of point cloud data, for example in domain adaptation...
Scientific, Seminar
PIHOT CRG Seminar: Bamdad Hosseini
October 21, 2021
Generative models such as Generative Adversarial Nets (GANs), Variational Autoencoders and Normalizing Flows have been very successful in the unsupervised learning task of generating samples from a high-dimensional probability distribution. However...
Scientific, Seminar
PIHOT CRG Seminar: Max Fathi
December 1, 2021
Stein’s method is a set of techniques for bounding distances between probability measures via integration-by-parts formulas. It was introduced by Stein in the 1980s for bouding the rate of convergence in central limit theorems, and has found many...
Scientific, Seminar
KI Seminar: Nathael Gozlan
January 27, 2022
Online
This talk will present the framework of weak optimal transport which allows to incorporate more general penalizations on elementary mass transports. After recalling general duality results and different optimality criteria, we will focus on recent...
Scientific, Seminar
KI Seminar: Marc Henry
February 24, 2022
Online
This talk focuses on the central role played by optimal transport theory in the study of incomplete econometric models. Incomplete econometric models are designed to analyze microeconomic data within the constraints of microeconomic theoretic...
Scientific, Seminar
KI Seminar: Anna Korba
March 17, 2022
Online
An important problem in machine learning and computational statistics is to sample from an intractable target distribution, e.g. to sample or compute functionals (expectations, normalizing constants) of the target distribution. This sampling problem...
Seminar
KI Seminar: Jan Obloj
April 28, 2022
Online
Wasserstein distances, or Optimal Transport methods more generally, offer a powerful non-parametric toolbox to conceptualise and quantify model uncertainty in diverse applications. Importantly, they work across the spectrum: from small uncertainty...
Scientific, Seminar
KI Seminar: Asuka Takatsu
June 26, 2022
Online
In optimal transport problems on a finite set, one successful approach to reducing its computational burden is the regularization by the Kullback-Leibler divergence. Then a natural question arises: Are other divergences not admissible for...
Scientific, Seminar
KI Seminar: Nabarun Deb
September 29, 2022
Online
The Wasserstein distance is a powerful tool in modern machine learning to metrize the space of probability distributions in a way that takes into account the geometry of the domain. Therefore, a lot of attention has been devoted in the literature to...
Professor of Mathematics, University of Washington
Professor of Mathematics, University of British Columbia
Associate Professor of Mathematics, University of Alberta