Alternatives and similar repositories for Graph-VAE

Users that are interested in Graph-VAE are comparing it to the libraries listed below

• wengong-jin / iclr19-graph2graph
  Learning Multimodal Graph-to-Graph Translation for Molecular Optimization (ICLR 2019)
  ☆150Updated 6 years ago
• rusty1s / himp-gnn
  Hierarchical Inter-Message Passing for Learning on Molecular Graphs
  ☆79Updated 3 years ago
• LingxiaoShawn / PairNorm
  Source code for PairNorm (ICLR 2020)
  ☆78Updated 5 years ago
• mims-harvard / G-Meta
  Graph meta learning via local subgraphs (NeurIPS 2020)
  ☆123Updated 11 months ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 6 years ago
• DeepGraphLearning / GraphAF
  ☆54Updated 3 years ago
• PurdueMINDS / RelationalPooling
  ☆35Updated 6 years ago
• Networks-Learning / nevae
  Code and data for "NeVAE: A Deep Generative Model for Molecular Graphs", AAAI 2019
  ☆54Updated 5 years ago
• KelestZ / CondGen
  Conditional Structure Generation through Graph Variational Generative Adversarial Nets, NeurIPS 2019.
  ☆54Updated 5 years ago
• Haggaim / InvariantGraphNetworks
  Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"
  ☆24Updated 5 years ago
• cvignac / SMP
  ☆28Updated 3 years ago
• plai-group / gae_in_pytorch
  Graph Auto-Encoder in PyTorch
  ☆81Updated 2 years ago
• claying / GCKN
  Pytorch Implementation of Graph Convolutional Kernel Networks
  ☆54Updated 2 years ago
• jliu / graph-normalizing-flows
  Code for Graph Normalizing Flows.
  ☆61Updated 5 years ago
• seokhokang / graphvae_approx
  Efficient Learning of Non-Autoregressive Graph Variational Autoencoders for Molecular Graph Generation
  ☆40Updated 4 years ago
• balcilar / Spectral-Designed-Graph-Convolutions
  Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper
  ☆50Updated 4 years ago
• benatorc / OTGNN
  OTGNN code
  ☆55Updated 5 years ago
• anonymous1025 / Deep-Graph-Translation-
  ☆16Updated 5 years ago
• Saro00 / DGN
  Implementation of Directional Graph Networks in PyTorch and DGL
  ☆118Updated 4 years ago
• Nate1874 / StructPool
  The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields
  ☆58Updated 5 years ago
• karl-zhao / benchmarking-gnns-pyg
  ☆31Updated 2 years ago
• benatorc / PA-Graph-Transformer
  ☆43Updated 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 3 months ago
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 4 years ago
• pfnet-research / graph-nvp
  GraphNVP: An Invertible Flow Model for Generating Molecular Graphs
  ☆93Updated 3 years ago
• vermaMachineLearning / Universal-Graph-Embedding-Neural-Network
  Paper Code Learning Powerful Graph Neural Network Embeddings With Aid Of Transfer Learning
  ☆40Updated 5 years ago
• amirkhas / GraphMemoryNet
  Memory-Based Graph Networks
  ☆103Updated 3 years ago
• se-ok / WLsimilarity
  informal exposition of Weisfeiler-Leman similarity
  ☆28Updated 4 years ago
• ermongroup / GraphScoreMatching
  Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling
  ☆110Updated last year
• ndey96 / GCNN-Explainability
  Implementation of "Explainability Methods for Graph Convolutional Neural Networks" from HRL Laboratories
  ☆83Updated 3 years ago