nerdslab / halfhopLinks
Official Implementation of Half-Hop
☆20Updated 2 years ago
Alternatives and similar repositories for halfhop
Users that are interested in halfhop are comparing it to the libraries listed below
Sorting:
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 3 years ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆33Updated 3 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 3 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆53Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 3 years ago
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆90Updated last year
- How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications (KDD'22)☆13Updated 3 years ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆44Updated 2 years ago
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆39Updated 2 years ago
- [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"☆46Updated 3 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆86Updated 10 months ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆106Updated 3 months ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- How Powerful are Spectral Graph Neural Networks☆73Updated 2 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 3 years ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated 2 years ago
- WWW2021: Interpreting and Unifying Graph Neural Networks with An Optimization Framework☆14Updated 4 years ago
- Node Dependent Local Smoothing for Scalable Graph Learning (NeurIPS'21, Spotlight)☆22Updated 3 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
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆32Updated last year
- The implementation for the NeurIPS 2022 paper Parameter-free Dynamic Graph Embedding for Link Prediction.☆16Updated 2 years ago
- [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 EvenNet.☆20Updated 2 years ago
- Graph Structured Neural Network☆40Updated 3 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆44Updated 3 years ago
- ☆38Updated 2 years ago
- ☆38Updated 3 years ago
- ☆12Updated last year