High-throughput single-cell profiling provides an unprecedented ability to uncover the
molecular states of millions of cells. These technologies are, however, destructive to cells …

Simulation-free methods for training continuous-time generative models construct probability
paths that go between noise distributions and individual data samples. Recent works, such …

Understanding and predicting molecular responses in single cells upon chemical, genetic or
mechanical perturbations is a core question in biology. Obtaining single-cell measurements …

Learning the continuous dynamics of a system from snapshots of its temporal marginals is a
problem which appears throughout natural sciences and machine learning, including in …

We consider the problem of estimating the optimal transport map between two probability
distributions, $ P $ and $ Q $ in $\mathbb {R}^ d $, on the basis of iid samples. All existing …

Optimal Transport (OT) problem investigates a transport map that bridges two distributions
while minimizing a given cost function. In this regard, OT between tractable prior distribution …

This paper focuses on computing the convex conjugate operation that arises when solving
Euclidean Wasserstein-2 optimal transport problems. This conjugation, which is also …

We investigate the optimal transport problem between probability measures when the
underlying cost function is understood to satisfy a least action principle, also known as a …

In many unpaired image domain translation problems, eg, style transfer or super-resolution,
it is important to keep the translated image similar to its respective input image. We propose …

Schr\" odinger bridges (SBs) provide an elegant framework for modeling the temporal
evolution of populations in physical, chemical, or biological systems. Such natural processes …