2 code implementations • 12 Mar 2023 • Jiajin Li, Jianheng Tang, Lemin Kong, Huikang Liu, Jia Li, Anthony Man-Cho So, Jose Blanchet
This observation allows us to provide an approximation bound for the distance between the fixed-point set of BAPG and the critical point set of GW.
1 code implementation • NeurIPS 2023 • Lemin Kong, Jiajin Li, Jianheng Tang, Anthony Man-Cho So
Gromov-Wasserstein (GW) distance is a powerful tool for comparing and aligning probability distributions supported on different metric spaces.
no code implementations • 17 May 2022 • Jiajin Li, Jianheng Tang, Lemin Kong, Huikang Liu, Jia Li, Anthony Man-Cho So, Jose Blanchet
In this paper, we study the design and analysis of a class of efficient algorithms for computing the Gromov-Wasserstein (GW) distance tailored to large-scale graph learning tasks.