We consider the sampling problem from a composite distribution whose
pot...
Data for pretraining machine learning models often consists of collectio...
We propose a sampling algorithm that achieves superior complexity bounds...
We study the problem of sampling from a target distribution in ℝ^d
whose...
The gradient flow of a function over the space of probability densities ...
Multi-marginal optimal transport (MOT) is a generalization of optimal
tr...
We present a new particle filtering algorithm for nonlinear systems in t...
Monge map refers to the optimal transport map between two probability
di...
Wasserstein Barycenter is a principled approach to represent the weighte...