TrustAGI-Lab / graph-deep-learningLinks
This repository summarises the open source codes of our group
☆27Updated 3 years ago
Alternatives and similar repositories for graph-deep-learning
Users that are interested in graph-deep-learning are comparing it to the libraries listed below
Sorting:
- Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"☆89Updated 4 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆68Updated 3 years ago
- The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)☆46Updated 5 years ago
- A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in …☆30Updated 4 years ago
- Source code for "Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation" (IJCAI 2020)☆17Updated last year
- Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"☆97Updated 2 years ago
- The implementation of our AAAI 2020 paper "GSSNN: Graph Smoothing Splines Neural Network".☆20Updated 5 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 4 years ago
- DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification☆29Updated 4 years ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆33Updated 4 years ago
- Variational Graph Convolutional Networks☆23Updated 5 years ago
- Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport☆37Updated 4 years ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆36Updated 4 years ago
- [IJCAI 2021] A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning".☆40Updated 3 years ago
- Implementation for Simple Spectral Graph Convolution in ICLR 2021☆85Updated 3 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆67Updated 3 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆118Updated 5 years ago
- Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction☆38Updated 3 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 4 years ago
- Hypergraph representation learning: Hypergraph Networks with Hyperedge Neurons.☆44Updated 5 years ago
- Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"☆59Updated 4 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆49Updated 3 years ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆102Updated 5 years ago
- The implementation of our ICDM 2019 paper "Relation Structure-Aware Heterogeneous Graph Neural Network" RSHN.☆18Updated 5 years ago
- Graph meta learning via local subgraphs (NeurIPS 2020)☆126Updated last year
- Graph Recurrent Networks with Attributed Random Walks☆28Updated 2 years ago
- Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism"☆61Updated 4 years ago
- PyTorch implementation of "Graph Convolutional Networks for Graphs Containing Missing Features"☆49Updated last year
- HDGI code☆63Updated 5 years ago
- The official code of WWW2021 paper: Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation …☆77Updated 4 years ago