snap-stanford / GraphRNNLinks
☆423Updated 6 years ago
Alternatives and similar repositories for GraphRNN
Users that are interested in GraphRNN are comparing it to the libraries listed below
Sorting:
- GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models☆722Updated 3 years ago
- Position-aware Graph Neural Networks☆399Updated 4 years ago
- ☆492Updated 4 years ago
- Implementation of the paper "NetGAN: Generating Graphs via Random Walks".☆195Updated 4 years ago
- Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019☆478Updated last year
- Graph Markov Neural Networks☆410Updated 5 years ago
- Deep Graph Infomax (https://arxiv.org/abs/1809.10341)☆645Updated 2 years ago
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆187Updated 3 years ago
- Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)☆285Updated 4 years ago
- Lanczos Network, Graph Neural Networks, Deep Graph Convolutional Networks, Deep Learning on Graph Structured Data, QM8 Quantum Chemistry …☆314Updated 5 years ago
- official implementation for the paper "Simplifying Graph Convolutional Networks"☆842Updated 3 years ago
- A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)☆535Updated 5 years ago
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆352Updated last month
- Multi-View Spectral Graph Convolution with Consistent Edge Attention for Molecular Modeling☆203Updated 3 years ago
- Hyperbolic Graph Neural Networks☆236Updated 5 years ago
- Framework for evaluating Graph Neural Network models on semi-supervised node classification task☆475Updated 6 years ago
- A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).☆273Updated 2 years ago
- ☆354Updated 2 years ago
- Graph Classification with Graph Convolutional Networks in PyTorch (NeurIPS 2018 Workshop)☆334Updated 4 years ago
- ☆300Updated 2 years ago
- Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" …☆318Updated last year
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆197Updated last year
- Hierarchical Graph Pooling with Structure Learning☆341Updated 4 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆272Updated 2 years ago
- The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""☆526Updated 4 years ago
- Representation learning on large graphs using stochastic graph convolutions.☆138Updated 7 years ago
- PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)☆322Updated 7 months ago
- A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)☆467Updated 5 years ago
- [DSAA 2018] Autoencoders for Link Prediction and Semi-Supervised Node Classification☆256Updated 5 years ago
- An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).☆405Updated 2 years ago