JiaxuanYou / P-GNNLinks
Position-aware Graph Neural Networks
☆399Updated 4 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:
- ☆497Updated 4 years ago
- ☆428Updated 6 years ago
- This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification☆473Updated 2 years ago
- ☆301Updated 3 years ago
- Deep Graph Infomax (https://arxiv.org/abs/1809.10341)☆649Updated 2 years ago
- Graph Markov Neural Networks☆411Updated 5 years ago
- Graph Classification with Graph Convolutional Networks in PyTorch (NeurIPS 2018 Workshop)☆335Updated 4 years ago
- Implementation of the paper "NetGAN: Generating Graphs via Random Walks".☆195Updated 4 years ago
- Official PyTorch Implementation of SAGPool - ICML 2019☆371Updated last year
- Framework for evaluating Graph Neural Network models on semi-supervised node classification task☆482Updated 6 years ago
- Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" …☆320Updated last year
- PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)☆321Updated 9 months ago
- official implementation for the paper "Simplifying Graph Convolutional Networks"☆845Updated 3 years ago
- Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)☆286Updated 4 years ago
- Representation learning on large graphs using stochastic graph convolutions.☆138Updated 7 years ago
- PyTorch implementation of "Simple and Deep Graph Convolutional Networks"☆356Updated 5 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆199Updated last year
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆189Updated 3 years ago
- GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models☆727Updated 3 years ago
- Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…☆125Updated 6 years ago
- The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""☆526Updated 4 years ago
- tensorflow-as-gcn☆90Updated 5 years ago
- [IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"☆123Updated last year
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆271Updated 2 years ago
- A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).☆801Updated 2 years ago
- [ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive L…☆496Updated 3 years ago
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆353Updated 3 months ago
- Distance Encoding for GNN Design☆187Updated 4 years ago
- A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).☆370Updated 2 years ago
- Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019☆477Updated 2 years ago