CUAI / Non-Homophily-BenchmarksLinks
[WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs
☆113Updated 3 years ago
Alternatives and similar repositories for Non-Homophily-Benchmarks
Users that are interested in Non-Homophily-Benchmarks are comparing it to the libraries listed below
Sorting:
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆123Updated 2 years ago
- ☆135Updated last year
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆80Updated last year
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆113Updated 9 months ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆103Updated last week
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆138Updated 7 months ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆88Updated 3 years ago
- How Powerful are Spectral Graph Neural Networks☆72Updated last year
- ☆76Updated 2 years ago
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆54Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- ☆54Updated 9 months ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆119Updated 2 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆89Updated 2 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆80Updated 3 years ago
- [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)☆92Updated 8 months ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆83Updated 7 months ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆80Updated 3 years ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆80Updated 4 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆116Updated 5 years ago
- Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"☆45Updated 3 years ago
- This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"☆98Updated last year
- Graph Structured Neural Network☆40Updated 2 years ago
- Dynamic Graph Benchmark☆81Updated 2 years ago
- ☆57Updated 3 years ago
- Papers about out-of-distribution generalization on graphs.☆166Updated 2 years ago
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆44Updated 6 months ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆85Updated 8 months ago