jianhao2016 / GPRGNNLinks
☆135Updated 2 years ago
Alternatives and similar repositories for GPRGNN
Users that are interested in GPRGNN 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
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆103Updated 3 weeks ago
- AAAI'21: Data Augmentation for Graph Neural Networks☆193Updated last year
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆56Updated 2 years ago
- ☆97Updated 4 years ago
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆113Updated 3 years ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆80Updated 4 years ago
- How Powerful are Spectral Graph Neural Networks☆73Updated last year
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆140Updated 8 months ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆84Updated 7 months ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆136Updated 2 years ago
- DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'☆65Updated last year
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆119Updated 2 years ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆113Updated 10 months ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆88Updated 3 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆58Updated 4 years ago
- Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…☆230Updated last year
- This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"☆100Updated last year
- ☆77Updated 4 years ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆80Updated last year
- Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"☆45Updated 3 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- The source code of HeCo☆166Updated 3 years ago
- Graph Structured Neural Network☆40Updated 2 years ago
- ☆75Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆116Updated 5 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆106Updated last year
- Parameterized Explainer for Graph Neural Network☆136Updated last year
- Node Dependent Local Smoothing for Scalable Graph Learning (NeurIPS'21, Spotlight)☆21Updated 3 years ago