2 papers
stat.ML2026
Radon--Wasserstein Gradient Flows for Interacting-Particle Sampling in High Dimensions
Elias Hess-Childs, Dejan Slepčev, Lantian Xu
Gradient flows of the Kullback--Leibler (KL) divergence, such as the Fokker--Planck equation and Stein Variational Gradient Descent, evolve a distribution toward a target density k…
cs.LG2024
A Geometry-Aware Algorithm to Learn Hierarchical Embeddings in Hyperbolic Space
Zhangyu Wang, Lantian Xu, Zhifeng Kong +3
Hyperbolic embeddings are a class of representation learning methods that offer competitive performances when data can be abstracted as a tree-like graph. However, in practice, lea…