3 citations · 4 across the 10 of their papers we have counts for
10 papers
Quantitative Stability of Many-Marginal Schrodinger Bridge
Rentian Yao, Young-Heon Kim, Geoffrey Schiebinger
In this paper, we explore quantitative stability of multi-marginal Schrödinger bridges with respect to the marginal constraints. We focus on the case where the number of marginal c…
Statistical Analysis of the Sinkhorn Iterations for Two-Sample Schrödinger Bridge Estimation
Ibuki Maeda, Rentian Yao, Atsushi Nitanda
The Schrödinger bridge problem seeks the optimal stochastic process that connects two given probability distributions with minimal energy modification. While the Sinkhorn algorithm…
Convergence Rate of the Solution of Multi-marginal Schrodinger Bridge Problem with Marginal Constraints from SDEs
Rentian Yao, Young--Heon Kim, Geoffrey Schiebinger
In this paper, we investigate the multi-marginal Schrodinger bridge (MSB) problem whose marginal constraints are marginal distributions of a stochastic differential equation (SDE)…
Learning Density Evolution from Snapshot Data
Rentian Yao, Atsushi Nitanda, Xiaohui Chen +1
Motivated by learning dynamical structures from static snapshot data, this paper presents a distribution-on-scalar regression approach for estimating the density evolution of a sto…
Optimal Transport Barycenter via Nonconvex-Concave Minimax Optimization
Kaheon Kim, Rentian Yao, Changbo Zhu +1
The optimal transport barycenter (a.k.a. Wasserstein barycenter) is a fundamental notion of averaging that extends from the Euclidean space to the Wasserstein space of probability…
Wasserstein Proximal Coordinate Gradient Algorithms
Rentian Yao, Xiaohui Chen, Yun Yang
Motivated by approximation Bayesian computation using mean-field variational approximation and the computation of equilibrium in multi-species systems with cross-interaction, this…
Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow
Rentian Yao, Linjun Huang, Yun Yang
Motivated by the computation of the non-parametric maximum likelihood estimator (NPMLE) and the Bayesian posterior in statistics, this paper explores the problem of convex optimiza…
A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
Yifan Chen, Rentian Yao, Yun Yang +1
Graph coarsening is a technique for solving large-scale graph problems by working on a smaller version of the original graph, and possibly interpolating the results back to the ori…
Mean-field Variational Inference via Wasserstein Gradient Flow
Rentian Yao, Yun Yang
Variational inference, such as the mean-field (MF) approximation, requires certain conjugacy structures for efficient computation. These can impose unnecessary restrictions on the…
Mean-Field Nonparametric Estimation of Interacting Particle Systems
Rentian Yao, Xiaohui Chen, Yun Yang
This paper concerns the nonparametric estimation problem of the distribution-state dependent drift vector field in an interacting -particle system. Observing single-trajectory d…