muhanzhang / DGCNNLinks
Code for "M. Zhang, Z. Cui, M. Neumann, and Y. Chen, An End-to-End Deep Learning Architecture for Graph Classification, AAAI-18".
☆178Updated 7 years ago
Alternatives and similar repositories for DGCNN
Users that are interested in DGCNN are comparing it to the libraries listed below
Sorting:
- PyTorch implementation of DGCNN☆389Updated last year
- [IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"☆122Updated last year
- Graph Classification with Graph Convolutional Networks in PyTorch (NeurIPS 2018 Workshop)☆334Updated 4 years ago
- Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…☆124Updated 5 years ago
- ☆491Updated 4 years ago
- This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., …☆184Updated 3 years ago
- [DSAA 2018] Autoencoders for Link Prediction and Semi-Supervised Node Classification☆255Updated 5 years ago
- ☆150Updated 5 years ago
- Official PyTorch Implementation of SAGPool - ICML 2019☆370Updated last year
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆271Updated 2 years ago
- ☆299Updated 2 years ago
- Multi-View Spectral Graph Convolution with Consistent Edge Attention for Molecular Modeling☆203Updated 3 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆195Updated last year
- NeurIPS 2019: HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs☆200Updated 4 years ago
- Graph Auto-Encoder in PyTorch☆81Updated 2 years ago
- Position-aware Graph Neural Networks☆399Updated 4 years ago
- DHGNN source code for IJCAI19 paper: "Dynamic Hypergraph Neural Networks"☆261Updated 2 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
- Multi-Graph Convolutional Neural Networks☆255Updated 7 years ago
- A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)☆210Updated 2 years ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆100Updated 5 years ago
- Hierarchical Graph Pooling with Structure Learning☆341Updated 3 years ago
- This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification☆472Updated 2 years ago
- PyTorch implementation of "Simple and Deep Graph Convolutional Networks"☆350Updated 4 years ago
- Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)☆285Updated 4 years ago
- Implementation of the paper "NetGAN: Generating Graphs via Random Walks".☆194Updated 4 years ago
- Representation learning on large graphs using stochastic graph convolutions.☆138Updated 7 years ago
- PyTorch Implementation of GraphTSNE, ICLR’19☆134Updated 6 years ago
- An implementation of KDD paper "Graph Convolutional Networks with EigenPooling"☆49Updated 5 years ago
- A PyTorch implementation of DGCNN based on AAAI 2018 paper "An End-to-End Deep Learning Architecture for Graph Classification"☆64Updated last year