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Estimation of smooth densities in Wasserstein distance
Niloy Biswas - Bounding Wasserstein distance with couplings
Wasserstein Distance to Independence Models
Wasserstein distance on graphs
Approximate Bayesian computation with the Wasserstein distance
Introduction to the Wasserstein distance
Julien Tierny (2/3/22): Wasserstein Distances, Geodesics and Barycenters of Merge Trees
Bernd Sturmfels, Wasserstein Distance to Independence Models, AlCoVE 2020
Wasserstein Distance: Metric Proof
Le Séminaire Palaisien | Boris Muzellec - «The Bures-Wasserstein Geometry for machine learning »
BayLearn 2021: Poster A-06: Intrinsic Sliced Wasserstein Distances on Manifolds and Graphs
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Last Updated: October 27, 2026
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In this video, Wojtek provides an overview of the Please consider supporting us on Patreon if you enjoy our content: patreon.com/thesyntheticmind What's the best way ... Speaker: James Murphy (Tufts University) Title: Intrinsically Low-Dimensional Models for Short talks by postdoctoral members Topic: Estimating the ... estimate of of WP or directly mu on you in this version This video was contributed to the workshop bayescomp-isba.github.io/measuringquality.html. Speaker: Moo K. Chung, University of Wisconsin-Madison Time/Place: POSTECH MINDS TDA/M&L WORKSHOP July 8, 2021 ... Christian Robert University of Warwick, UK and Université Paris-Dauphine, France. In this talk, I will present a unified computational framework for the estimation of We prove that W_p is a metric. Can be found in Villani's books. Le Séminaire Palaisien réunit, chaque premier mardi du mois, la vaste communauté de recherche de Saclay autour de la ... Collections of probability distributions arise in a variety of statistical applications ranging from user activity pattern
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