1 citations · 2 across the 5 of their papers we have counts for
5 papers
Solving high-dimensional Kolmogorov backward equations with functional hierarchical tensor operators
Xun Tang, Leah Collis, Lexing Ying
Solving high-dimensional partial differential equations necessitates methods free of exponential scaling in the dimension of the problem. This work introduces a tensor network appr…
A Sinkhorn-type Algorithm for Constrained Optimal Transport
Xun Tang, Holakou Rahmanian, Michael Shavlovsky +3
Entropic optimal transport (OT) and the Sinkhorn algorithm have made it practical for machine learning practitioners to perform the fundamental task of calculating transport distan…
Accelerating Sinkhorn Algorithm with Sparse Newton Iterations
Xun Tang, Michael Shavlovsky, Holakou Rahmanian +4
Computing the optimal transport distance between statistical distributions is a fundamental task in machine learning. One remarkable recent advancement is entropic regularization a…
Generative Modeling via Tree Tensor Network States
Xun Tang, Yoonhaeng Hur, Yuehaw Khoo +1
In this paper, we present a density estimation framework based on tree tensor-network states. The proposed method consists of determining the tree topology with Chow-Liu algorithm,…
Endogeneity in Weakly Separable Models without Monotonicity
Songnian Chen, Shakeeb Khan, Xun Tang
We identify and estimate treatment effects when potential outcomes are weakly separable with a binary endogenous treatment. Vytlacil and Yildiz (2007) proposed an identification st…