TrustAGI-Lab / ARGA
This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., Hu, R., Long, G., Jiang, J., Yao, L., & Zhang, C. (2018). Adversarially Regularized Graph Autoencoder for Graph Embedding, [https://www.ijcai.org/proceedings/2018/0362.pdf].
☆184Updated 3 years ago
Alternatives and similar repositories for ARGA:
Users that are interested in ARGA are comparing it to the libraries listed below
- Graph Auto-Encoder in PyTorch☆81Updated 2 years ago
- Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…☆124Updated 5 years ago
- This is the implementation of paper 'Variational Graph Auto-Encoder' in NIPS Workshop on Bayesian Deep Learning, 2016.☆74Updated 6 years ago
- [IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"☆121Updated last year
- Implementation of the paper "NetGAN: Generating Graphs via Random Walks".☆193Updated 4 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆115Updated 5 years ago
- Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R…☆132Updated 4 years ago
- ☆137Updated 4 years ago
- Implementation of Graph Convolutional Networks in TensorFlow☆45Updated 7 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆194Updated last year
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆271Updated 2 years ago
- Multi-Graph Convolutional Neural Networks☆255Updated 7 years ago
- Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…☆227Updated last year
- [DSAA 2018] Autoencoders for Link Prediction and Semi-Supervised Node Classification☆255Updated 5 years ago
- Representation learning on large graphs using stochastic graph convolutions.☆138Updated 6 years ago
- Dual Graph Convolution Networks☆95Updated 6 years ago
- Multi-View Spectral Graph Convolution with Consistent Edge Attention for Molecular Modeling☆203Updated 3 years ago
- tensorflow-as-gcn☆91Updated 5 years ago
- Implementation of "GraphSGAN", a GAN-based semi-supervised learning algorithm for graph data.☆86Updated 5 years ago
- Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"☆210Updated last year
- Code for "M. Zhang, Z. Cui, M. Neumann, and Y. Chen, An End-to-End Deep Learning Architecture for Graph Classification, AAAI-18".☆178Updated 6 years ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆100Updated 4 years ago
- Source code and dataset for KDD 2020 paper "Adaptive Graph Encoder for Attributed Graph Embedding"☆114Updated last year
- Unsupervised Attributed Multiplex Network Embedding (AAAI 2020)☆148Updated 2 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆155Updated 2 years ago
- Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" …☆319Updated last year
- ☆296Updated 2 years ago
- ☆29Updated 4 years ago
- Graph Auto-Encoder in PyTorch☆432Updated last year
- [ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision☆156Updated 2 years ago