danielzuegner / netgan
Implementation of the paper "NetGAN: Generating Graphs via Random Walks".
☆193Updated 4 years ago
Alternatives and similar repositories for netgan:
Users that are interested in netgan are comparing it to the libraries listed below
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆194Updated last year
- Graph Auto-Encoder in PyTorch☆81Updated last year
- This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., …☆184Updated 3 years ago
- tensorflow-as-gcn☆92Updated 5 years ago
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆187Updated 3 years ago
- Implementation of "GraphSGAN", a GAN-based semi-supervised learning algorithm for graph data.☆86Updated 5 years ago
- Position-aware Graph Neural Networks☆399Updated 4 years ago
- Multi-Graph Convolutional Neural Networks☆253Updated 6 years ago
- ☆421Updated 6 years ago
- Representation learning on large graphs using stochastic graph convolutions.☆138Updated 6 years ago
- ☆136Updated 4 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆270Updated last year
- Stochastic training of graph convolutional networks☆84Updated 2 years ago
- Conditional Structure Generation through Graph Variational Generative Adversarial Nets, NeurIPS 2019.☆54Updated 5 years ago
- Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…☆123Updated 5 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆155Updated 2 years ago
- Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"☆76Updated 2 years ago
- This is the implementation of paper 'Variational Graph Auto-Encoder' in NIPS Workshop on Bayesian Deep Learning, 2016.☆75Updated 6 years ago
- Gaussian node embeddings. Implementation of "Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking".☆174Updated last year
- Distance Encoding for GNN Design☆187Updated 4 years ago
- PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)☆321Updated 3 months ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆100Updated 4 years ago
- Graph convolutional recurrent neural network☆179Updated 7 years ago
- [DSAA 2018] Autoencoders for Link Prediction and Semi-Supervised Node Classification☆255Updated 5 years ago
- [IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"☆121Updated 10 months ago
- Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" …☆318Updated last year
- Official code for "vGraph: A Generative Model for Joint CommunityDetection and Node Representation Learning" (NeurIPS 2019)☆45Updated last year
- Code for Graphite iterative graph generation☆59Updated 5 years ago
- Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".☆146Updated 3 years ago
- Source code for PairNorm (ICLR 2020)☆76Updated 4 years ago