Facundo Memoli

2 accepted papers

2022

Weisfeiler-Lehman Meets Gromov-Wasserstein

Samantha Chen, Sunhyuk Lim, Facundo Memoli, Zhengchao Wan, Yusu Wang

ICML 2022spotlight

The Weisfeiler-Lehman (WL) test is a classical procedure for graph isomorphism testing. The WL test has also been widely used both for designing graph kernels and for analyzing graph neural networks. In this paper, we propose the Weisfeiler-Lehman (WL) distance, a notion of distance between labeled…

Cited by 29 Source ↗PDF ↗code ↗Scholar ↗

2019

The Wasserstein Transform

Facundo Memoli, Zane Smith, Zhengchao Wan

ICML 2019oral

We introduce the Wasserstein transform, a method for enhancing and denoising datasets defined on general metric spaces. The construction draws inspiration from Optimal Transportation ideas. We establish the stability of our method under data perturbation and, when the dataset is assumed to be Euclid…

Cited by 11 Source ↗PDF ↗Scholar ↗