Tam Le

11

Papers

7

Total Citations

Papers (11)

Tree-Sliced Wasserstein Distance with Nonlinear Projection

Scalable Sobolev IPM for Probability Measures on a Graph

Generalized Sobolev Transport for Probability Measures on a Graph

Sliced Wasserstein with Random-Path Projecting Directions

Point-Set Distances for Learning Representations of 3D Point Clouds

Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations

Safe Grid Search with Optimal Complexity

Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams

Tree-Sliced Variants of Wasserstein Distances

Nonsmooth Implicit Differentiation for Machine-Learning and Optimization

Adversarial Regression with Doubly Non-negative Weighting Matrices