CUAI / Non-Homophily-Large-ScaleLinks
[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
☆123Updated 3 years ago
Alternatives and similar repositories for Non-Homophily-Large-Scale
Users that are interested in Non-Homophily-Large-Scale are comparing it to the libraries listed below
Sorting:
- ☆139Updated 2 years ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆121Updated 2 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆107Updated 7 months ago
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆115Updated 4 years ago
- ☆79Updated 3 years ago
- Parameterized Explainer for Graph Neural Network☆142Updated last year
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆92Updated 4 years ago
- ☆60Updated last year
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆82Updated 4 years ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆136Updated last year
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆56Updated 2 years ago
- The source code of HeCo☆171Updated 3 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆46Updated 3 years ago
- ☆101Updated 4 years ago
- This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"☆104Updated 2 years ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆85Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆88Updated last year
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆60Updated 2 years ago
- ☆50Updated last year
- [ICLR'22][KDD'22][IJCAI'24][NeurIPS'25] Implementation of "Graph Condensation for Graph Neural Networks"☆141Updated 3 months ago
- ☆27Updated 3 years ago
- Code of GAMLP for Open Graph Benchmark. KDD‘22☆63Updated 3 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆59Updated 4 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆104Updated last year
- Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"☆46Updated 4 years ago
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆65Updated last year
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆42Updated 2 years ago
- How Powerful are Spectral Graph Neural Networks☆75Updated 2 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆116Updated last year