jiaqima / G3NNLinks
A Flexible Generative Framework for Graph-based Semi-supervised Learning (NeurIPS 2019)
☆16Updated 3 years ago
Alternatives and similar repositories for G3NN
Users that are interested in G3NN are comparing it to the libraries listed below
Sorting:
- Variational Graph Convolutional Networks☆23Updated 4 years ago
- The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)☆46Updated 4 years ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆35Updated 3 years ago
- Source code for PairNorm (ICLR 2020)☆77Updated 5 years ago
- AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)☆46Updated 3 years ago
- The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields☆58Updated 5 years ago
- [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆21Updated 2 years ago
- Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)☆34Updated 4 years ago
- [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆110Updated 3 years ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆68Updated last year
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆38Updated 4 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- Official PyTorch implementation for the following KDD2022 paper: Variational Inference for Training Graph Neural Networks in Low-Data Re…☆20Updated 2 years ago
- [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks☆27Updated 2 years ago
- Official code for the CVPR 2022 (oral) paper "OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.…☆34Updated 3 years ago
- Code for reproducing results in GraphMix paper☆72Updated 2 years ago
- ☆62Updated 4 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 2 years ago
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- Code for paper "Mixup for Node and Graph Classification", WWW 2021☆47Updated 4 years ago
- Code for "Explainability methods for graph convolutional neural networks" - PE Pope*, S Kolouri*, M Rostami, CE Martin, H Hoffmann (CVPR …☆34Updated 2 months ago
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆43Updated 2 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆58Updated last year
- First and Complementary Neighborhood Combination of Adjacency Matrix for Graph Learning☆20Updated last year
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- Collection of resources related with Graph Contrastive Learning.☆34Updated 4 years ago
- The official pytorch implementation of Propagation_then_Training for graph (https://arxiv.org/abs/2010.12408)☆26Updated 3 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆80Updated 3 years ago
- Implementation of "Bag of Tricks for Node Classification with Graph Neural Networks" based on DGL☆35Updated 4 months ago