GAP: Generalizable Approximate Graph Partitioning Framework

2 March 2019

Papers citing "GAP: Generalizable Approximate Graph Partitioning Framework"

6 / 6 papers shown

Title
NodeNAS: Node-Specific Graph Neural Architecture Search for Out-of-Distribution Generalization Qiyi Wang Yinning Shao Yunlong Ma Min Liu OOD 77 0 0 04 Mar 2025
Solving the Kidney-Exchange Problem via Graph Neural Networks with No Supervision P. F. Pimenta Pedro H. C. Avelar Luís C. Lamb 25 1 0 19 Apr 2023
Machine Learning-based Selection of Graph Partitioning Strategy Using the Characteristics of Graph Data and Algorithm Youngjoon Park Dongkyu Lee Tien-Cuong Bui 13 1 0 09 Sep 2022
Semi-relaxed Gromov-Wasserstein divergence with applications on graphs Cédric Vincent-Cuaz Rémi Flamary Marco Corneli Titouan Vayer Nicolas Courty OT 40 23 0 06 Oct 2021
Graph Learning for Combinatorial Optimization: A Survey of State-of-the-Art Yun Peng Byron Choi Jianliang Xu 25 5 0 26 Aug 2020
Adversarial Attack on Community Detection by Hiding Individuals Jia Li Honglei Zhang Zhichao Han Yu Rong Hong Cheng Junzhou Huang AAML 25 87 0 22 Jan 2020