inyeoplee77 / SAGPool
Official PyTorch Implementation of SAGPool - ICML 2019
☆371Updated last year
Alternatives and similar repositories for SAGPool:
Users that are interested in SAGPool are comparing it to the libraries listed below
- Graph Classification with Graph Convolutional Networks in PyTorch (NeurIPS 2018 Workshop)☆332Updated 4 years ago
- ☆487Updated 4 years ago
- This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification☆470Updated 2 years ago
- Deep Graph Infomax (https://arxiv.org/abs/1809.10341)☆637Updated 2 years ago
- Position-aware Graph Neural Networks☆400Updated 4 years ago
- Pytorch implementation of Graph U-Nets (ICML19)☆534Updated 4 years ago
- Graph Auto-Encoder in PyTorch☆430Updated last year
- PyTorch implementation of "Simple and Deep Graph Convolutional Networks"☆346Updated 4 years ago
- Pytorch Implementation for Graph Convolutional Neural Networks☆326Updated 6 years ago
- Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)☆284Updated 4 years ago
- official implementation for the paper "Simplifying Graph Convolutional Networks"☆840Updated 3 years ago
- Hierarchical Graph Pooling with Structure Learning☆339Updated 3 years ago
- ☆295Updated 2 years ago
- AM-GCN: Adaptive Multi-channel Graph Convolutional Networks☆235Updated 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
- PyTorch implementation of DGCNN☆379Updated last year
- Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" …☆318Updated last year
- Framework for evaluating Graph Neural Network models on semi-supervised node classification task☆472Updated 6 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆270Updated last year
- The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""☆524Updated 4 years ago
- Graph Convolution Network for PyTorch☆400Updated 5 years ago
- [IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"☆121Updated 11 months ago
- Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org☆1,159Updated 2 years ago
- Code for "M. Zhang, Z. Cui, M. Neumann, and Y. Chen, An End-to-End Deep Learning Architecture for Graph Classification, AAAI-18".☆177Updated 6 years ago
- A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).☆799Updated 2 years ago
- [GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)☆325Updated 11 months ago
- How Powerful are Graph Neural Networks?☆1,213Updated 3 years ago
- Graph Neural Network with Hierarchical Pooling for PyTorch: "Hierarchical Graph Representation Learning with Differentiable Pooling".☆77Updated 5 years ago
- NeurIPS 2019: HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs☆195Updated 4 years ago
- Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)☆1,017Updated 2 years ago