dongkwan-kim / SuperGAT
[ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
☆152Updated last year
Related projects ⓘ
Alternatives and complementary repositories for SuperGAT
- Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"☆208Updated last year
- ☆258Updated 2 years ago
- Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…☆223Updated last year
- Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"☆89Updated 3 years ago
- AAAI'21: Data Augmentation for Graph Neural Networks☆187Updated 6 months ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆111Updated 4 years ago
- ☆93Updated 3 years ago
- [GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)☆312Updated 6 months ago
- DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'☆63Updated 11 months ago
- ☆29Updated 4 years ago
- Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"☆97Updated last year
- Implementation for Simple Spectral Graph Convolution in ICLR 2021☆82Updated 2 years ago
- Unsupervised Attributed Multiplex Network Embedding (AAAI 2020)☆147Updated last year
- [WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"☆163Updated 6 months ago
- Source code and dataset for KDD 2020 paper "Adaptive Graph Encoder for Attributed Graph Embedding"☆109Updated last year
- Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"☆60Updated 3 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆85Updated 2 years ago
- ☆73Updated 3 years ago
- NeurIPS 2019: HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs☆185Updated 4 years ago
- A dgl implementation of Jumping Knowledge Networks (arXiv 1806.03536)☆39Updated 5 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆86Updated 3 years ago
- The official code of WWW2021 paper: Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation …☆73Updated 3 years ago
- ☆132Updated last year
- The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields☆57Updated 4 years ago
- Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"☆283Updated last year
- Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"☆42Updated 2 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆154Updated 2 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆267Updated last year
- Source code of AAAI21-Heterogeneous Graph Structure Learning for Graph Neural Networks☆113Updated 2 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆128Updated last year