3 papers
cs.LG2025
Differentially Private Wasserstein Barycenters
Anming Gu, Sasidhar Kunapuli, Mark Bun +2
The Wasserstein barycenter is defined as the mean of a set of probability measures under the optimal transport metric, and has numerous applications spanning machine learning, stat…
cs.LG2025
Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics
Anming Gu, Edward Chien, Kristjan Greenewald
We provide an algorithm to privately generate continuous-time data (e.g. marginals from stochastic differential equations), which has applications in highly sensitive domains invol…
cs.LG2025
Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior
Anming Gu, Edward Chien, Kristjan Greenewald
Trajectory inference seeks to recover the temporal dynamics of a population from snapshots of its (uncoupled) temporal marginals, i.e. where observed particles are not tracked over…