SitaoLuan / When-Do-GNNs-HelpLinks
Official repository for NeurIPS 2023 paper "When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability"
☆21Updated 9 months ago
Alternatives and similar repositories for When-Do-GNNs-Help
Users that are interested in When-Do-GNNs-Help are comparing it to the libraries listed below
Sorting:
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆85Updated 9 months ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆52Updated 2 years ago
- The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-pron…☆15Updated 2 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆44Updated 3 years ago
- Reimplementation of AAAI21 paper "Beyond Low-frequency Information in Graph Convolutional Networks" based on PyTorch and PyTorch Geometri…☆23Updated 2 years ago
- A collection of papers on Graph Structural Learning (GSL)☆56Updated last year
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆37Updated 3 years ago
- The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).☆45Updated last year
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆43Updated 2 years ago
- Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.☆34Updated 2 years ago
- A curated list of Heterophilous Graph Self-Supervised Learning papers.☆15Updated 2 years ago
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆38Updated 2 years ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆42Updated 2 years ago
- ☆49Updated 2 years ago
- Code for GBK-GNN (paper accepted by WWW2022)☆16Updated 3 years ago
- [ICML 2023] Linkless Link Prediction via Relational Distillation☆24Updated last year
- [WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhe…☆39Updated last year
- PyTorch implementation of "Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited"☆41Updated last year
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆119Updated 2 years ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- Pytorch implementation of EvenNet.☆20Updated 2 years ago
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆33Updated last year
- ☆59Updated 9 months ago
- ☆38Updated 3 years ago
- [WWW2024 Oral paper] "Graph Out-of-Distribution Generalization via Causal Intervention”.☆27Updated 10 months ago
- PyTorch implementation of "PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters"☆15Updated last year
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆143Updated 2 years ago
- The source code of SpCo☆35Updated 2 years ago