On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks

8 June 2023

Papers citing "On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks"

9 / 9 papers shown

Title
Understanding GNNs and Homophily in Dynamic Node Classification Michael Ito Danai Koutra Jenna Wiens 68 1 0 29 Apr 2025
Learning Laplacian Positional Encodings for Heterophilous Graphs Michael Ito Jiong Zhu Dexiong Chen Danai Koutra Jenna Wiens 74 1 0 29 Apr 2025
Unveiling the Impact of Local Homophily on GNN Fairness: In-Depth Analysis and New Benchmarks Donald Loveland Danai Koutra 23 1 0 05 Oct 2024
Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why? Jin Huang Xingjian Zhang Qiaozhu Mei Jiaqi Ma 12 13 0 28 Sep 2023
GraphWorld: Fake Graphs Bring Real Insights for GNNs John Palowitch Anton Tsitsulin Brandon Mayer Bryan Perozzi GNN 177 68 0 28 Feb 2022
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 84 445 0 04 Jan 2021
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 167 1,058 0 13 Feb 2020
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 139 828 0 28 Sep 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 283 4,143 0 23 Aug 2019