JiaxuanYou / P-GNNLinks
Position-aware Graph Neural Networks
☆402Updated 5 years ago
Alternatives and similar repositories for P-GNN
Users that are interested in P-GNN are comparing it to the libraries listed below
Sorting:
- ☆504Updated 5 years ago
- ☆432Updated 6 years ago
- Graph Markov Neural Networks☆411Updated 5 years ago
- ☆302Updated 3 years ago
- This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification☆476Updated 3 years ago
- Deep Graph Infomax (https://arxiv.org/abs/1809.10341)☆661Updated 3 years ago
- Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)☆289Updated 5 years ago
- PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)☆322Updated last year
- Framework for evaluating Graph Neural Network models on semi-supervised node classification task☆491Updated 7 years ago
- Graph Classification with Graph Convolutional Networks in PyTorch (NeurIPS 2018 Workshop)☆337Updated 5 years ago
- Official PyTorch Implementation of SAGPool - ICML 2019☆372Updated 2 years ago
- PyTorch implementation of "Simple and Deep Graph Convolutional Networks"☆358Updated 5 years ago
- GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models☆735Updated 4 years ago
- Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" …☆324Updated 2 years ago
- The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""☆528Updated 4 years ago
- official implementation for the paper "Simplifying Graph Convolutional Networks"☆847Updated 4 years ago
- Representation learning on large graphs using stochastic graph convolutions.☆143Updated 7 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆200Updated last year
- Implementation of the paper "NetGAN: Generating Graphs via Random Walks".☆198Updated 5 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆273Updated 2 years ago
- Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…☆125Updated 6 years ago
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆189Updated 3 years ago
- A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)☆540Updated 6 years ago
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆356Updated 7 months ago
- Distance Encoding for GNN Design☆188Updated 4 years ago
- [ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive L…☆503Updated 3 years ago
- Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019☆479Updated 2 years ago
- A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).☆373Updated 3 years ago
- An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).☆404Updated 3 years ago
- This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., …☆187Updated 3 years ago