290 citations · 1.8k across the 59 of their papers we have counts for
46 papers · 1 filter
Statistical optimal transport
Sinho Chewi, Jonathan Niles-Weed, Philippe Rigollet
We present an introduction to the field of statistical optimal transport, based on lectures given at École d'Été de Probabilités de Saint-Flour XLIX.
High-Dimensional Statistics
Philippe Rigollet, Jan-Christian Hütter
These lecture notes were written for the course 18.657, High Dimensional Statistics at MIT. They build on a set of notes that was prepared at Princeton University in 2013-14 that w…
Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow
Yuling Yan, Kaizheng Wang, Philippe Rigollet
Gaussian mixture models form a flexible and expressive parametric family of distributions that has found applications in a wide variety of applications. Unfortunately, fitting thes…
On the Approximation Accuracy of Gaussian Variational Inference
Anya Katsevich, Philippe Rigollet
The main computational challenge in Bayesian inference is to compute integrals against a high-dimensional posterior distribution. In the past decades, variational inference (VI) ha…
On the sample complexity of entropic optimal transport
Philippe Rigollet, Austin J. Stromme
We study the sample complexity of entropic optimal transport in high dimensions using computationally efficient plug-in estimators. We significantly advance the state of the art by…
The query complexity of sampling from strongly log-concave distributions in one dimension
Sinho Chewi, Patrik Gerber, Chen Lu +2
We establish the first tight lower bound of on the query complexity of sampling from the class of strongly log-concave and log-smooth distributions with condition nu…