Characterizing Graph Datasets for Node Classification:
Homophily-Heterophily Dichotomy and Beyond

Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond

13 September 2022

Denis Kuznedelev

Liudmila Prokhorenkova

Papers citing "Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond"

9 / 9 papers shown

Title
Rethinking Graph Contrastive Learning through Relative Similarity Preservation Zhiyuan Ning Pengfei Wang Ziyue Qiao Pengyang Wang Yuanchun Zhou 16 0 0 08 May 2025
Understanding GNNs and Homophily in Dynamic Node Classification Michael Ito Danai Koutra Jenna Wiens 68 1 0 29 Apr 2025
Mixture of Experts for Node Classification Yu Shi Yiqi Wang WeiXuan Lang Jiaxin Zhang Pan Dong Aiping Li 79 0 0 30 Nov 2024
Node-wise Filtering in Graph Neural Networks: A Mixture of Experts Approach Haoyu Han Juanhui Li Wei Huang Xianfeng Tang Hanqing Lu Chen Luo Hui Liu Jiliang Tang 25 5 0 05 Jun 2024
Contextualized Messages Boost Graph Representations Brian Godwin Lim Galvin Brice Lim Renzo Roel Tan Kazushi Ikeda AI4CE 36 1 0 19 Mar 2024
Good Classification Measures and How to Find Them Martijn Gösgens A. Zhiyanov Alexey Tikhonov Liudmila Prokhorenkova 22 22 0 22 Jan 2022
Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings Benedek Rozemberczki Rik Sarkar 101 52 0 08 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