Alternatives and similar repositories for CondGen:

Users that are interested in CondGen are comparing it to the libraries listed below

• LingxiaoShawn / PairNorm
  Source code for PairNorm (ICLR 2020)
  ☆76Updated 4 years ago
• zpeng27 / GMI
  Graph Representation Learning via Graphical Mutual Information Maximization
  ☆113Updated 4 years ago
• Shen-Lab / SS-GCNs
  [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
  ☆110Updated 3 years ago
• danielzuegner / netgan
  Implementation of the paper "NetGAN: Generating Graphs via Random Walks".
  ☆194Updated 4 years ago
• plai-group / gae_in_pytorch
  Graph Auto-Encoder in PyTorch
  ☆81Updated last year
• Nate1874 / StructPool
  The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields
  ☆57Updated 4 years ago
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 4 years ago
• yifan-h / CS-GNN
  Measuring and Improving the Use of Graph Information in Graph Neural Networks
  ☆82Updated 6 months ago
• idea-iitd / graphgen
  GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation
  ☆51Updated last year
• PurdueMINDS / RelationalPooling
  ☆35Updated 5 years ago
• mengliu1998 / DeeperGNN
  Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]
  ☆155Updated 2 years ago
• ppope / explain_graphs
  Code for "Explainability methods for graph convolutional neural networks" - PE Pope*, S Kolouri*, M Rostami, CE Martin, H Hoffmann (CVPR …
  ☆34Updated 6 months ago
• samihaija / mixhop
  Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…
  ☆123Updated 5 years ago
• AvigdorZ / ADaptive-Structural-Fingerprint
  ☆29Updated 4 years ago
• acbull / LADIES
  Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"
  ☆76Updated 2 years ago
• ChandlerBang / SelfTask-GNN
  Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
  ☆97Updated last year
• amirkhas / GraphMemoryNet
  Memory-Based Graph Networks
  ☆101Updated 2 years ago
• lucfra / LDS-GNN
  Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)
  ☆194Updated 11 months ago
• VoVAllen / diffpool
  ☆37Updated 5 years ago
• vikasverma1077 / GraphMix
  Code for reproducing results in GraphMix paper
  ☆72Updated 2 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆51Updated 4 years ago
• joeybose / Meta-Graph
  Meta-Learning for Few Shot Link Prediction
  ☆49Updated 4 years ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 5 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 4 years ago
• sunfanyunn / vGraph
  Official code for "vGraph: A Generative Model for Joint CommunityDetection and Node Representation Learning" (NeurIPS 2019)
  ☆45Updated last year
• mmiller96 / netgan_pytorch
  ☆28Updated last year
• mims-harvard / G-Meta
  Graph meta learning via local subgraphs (NeurIPS 2020)
  ☆120Updated 6 months ago
• VGraphRNN / VGRNN
  Variational Graph Recurrent Neural Networks - PyTorch
  ☆116Updated 4 years ago
• matenure / OTCoarsening
  Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
  ☆36Updated 3 years ago
• limaosen0 / Variational-Graph-Auto-Encoders
  This is the implementation of paper 'Variational Graph Auto-Encoder' in NIPS Workshop on Bayesian Deep Learning, 2016.
  ☆74Updated 6 years ago