Alternatives and similar repositories for graph-representation-learning:

Users that are interested in graph-representation-learning are comparing it to the libraries listed below

• TrustAGI-Lab / ARGA
  This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., …
  ☆185Updated 2 years ago
• fmonti / mgcnn
  Multi-Graph Convolutional Neural Networks
  ☆252Updated 6 years ago
• abojchevski / graph2gauss
  Gaussian node embeddings. Implementation of "Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking".
  ☆174Updated last year
• palash1992 / DynamicGEM
  ☆348Updated 4 years ago
• deezer / linear_graph_autoencoders
  Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R…
  ☆132Updated 4 years ago
• benedekrozemberczki / GAM
  A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).
  ☆271Updated 2 years ago
• muhanzhang / DGCNN
  Code for "M. Zhang, Z. Cui, M. Neumann, and Y. Chen, An End-to-End Deep Learning Architecture for Graph Classification, AAAI-18".
  ☆174Updated 6 years ago
• youngjoo-epfl / gconvRNN
  Graph convolutional recurrent neural network
  ☆179Updated 6 years ago
• benedekrozemberczki / SEAL-CI
  A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)
  ☆208Updated 2 years ago
• JiaxuanYou / P-GNN
  Position-aware Graph Neural Networks
  ☆398Updated 4 years ago
• bkj / pytorch-graphsage
  Representation learning on large graphs using stochastic graph convolutions.
  ☆139Updated 6 years ago
• snap-stanford / graphwave
  ☆172Updated 6 years ago
• leowyy / GraphTSNE
  PyTorch Implementation of GraphTSNE, ICLR’19
  ☆134Updated 5 years ago
• GTmac / HARP
  Code for the AAAI 2018 Paper "HARP: Hierarchical Representation Learning for Networks"
  ☆115Updated last year
• shchur / gnn-benchmark
  Framework for evaluating Graph Neural Network models on semi-supervised node classification task
  ☆462Updated 6 years ago
• benedekrozemberczki / AttentionWalk
  A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
  ☆324Updated 2 years ago
• samihaija / mixhop
  Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…
  ☆123Updated 5 years ago
• DeepGraphLearning / GMNN
  Graph Markov Neural Networks
  ☆404Updated 4 years ago
• plai-group / gae_in_pytorch
  Graph Auto-Encoder in PyTorch
  ☆81Updated last year
• gasteigerjo / ppnp
  PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)
  ☆321Updated 2 months ago
• lucfra / LDS-GNN
  Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)
  ☆194Updated 11 months ago
• matenure / FastGCN
  The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""
  ☆521Updated 3 years ago
• nd7141 / AWE
  Compute graph embeddings via Anonymous Walk Embeddings
  ☆82Updated 6 years ago
• MichSchli / RelationPrediction
  Implementation of R-GCNs for Relational Link Prediction
  ☆452Updated last year
• Luckick / EAGCN
  Multi-View Spectral Graph Convolution with Consistent Edge Attention for Molecular Modeling
  ☆202Updated 3 years ago
• muhanzhang / LinkPrediction
  Code for "M. Zhang, Y. Chen, Weisfeiler-Lehman Neural Machine for Link Prediction, KDD 2017 oral"
  ☆55Updated 6 years ago
• benedekrozemberczki / SGCN
  A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).
  ☆271Updated last year
• xptree / NetMF
  Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec
  ☆185Updated 5 years ago
• TrustAGI-Lab / graph_datasets
  A Repository of Benchmark Graph Datasets for Graph Classification (31 Graph Datasets In Total).
  ☆289Updated 2 years ago
• danielzuegner / netgan
  Implementation of the paper "NetGAN: Generating Graphs via Random Walks".
  ☆194Updated 4 years ago