Alternatives and similar repositories for Understanding-GCN

Users that are interested in Understanding-GCN are comparing it to the libraries listed below

• PurdueMINDS / RelationalPooling
  ☆35Updated 6 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆53Updated 5 years ago
• LingxiaoShawn / PairNorm
  Source code for PairNorm (ICLR 2020)
  ☆79Updated 5 years ago
• vikasverma1077 / GraphMix
  Code for reproducing results in GraphMix paper
  ☆72Updated 2 years ago
• divelab / DeeperGNN
  Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]
  ☆69Updated 2 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 5 years ago
• delta2323 / gnn-asymptotics
  Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.
  ☆30Updated 5 years ago
• mengliu1998 / DeeperGNN
  Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]
  ☆155Updated 2 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 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
• se-ok / WLsimilarity
  informal exposition of Weisfeiler-Leman similarity
  ☆28Updated 4 years ago
• PwnerHarry / Stronger_GCN
  Implementations of "Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks"
  ☆53Updated 10 months ago
• zhengdao-chen / GNN4CD
  Supervised community detection with line graph neural networks
  ☆89Updated 4 years ago
• malllabiisc / ConfGCN
  AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
  ☆59Updated 6 years ago
• yifan-h / CS-GNN
  Measuring and Improving the Use of Graph Information in Graph Neural Networks
  ☆83Updated last year
• matenure / OTCoarsening
  Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
  ☆37Updated 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 4 years ago
• malllabiisc / ASAP
  AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
  ☆100Updated 5 years ago
• ChandlerBang / SelfTask-GNN
  Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
  ☆97Updated 2 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
• claying / GCKN
  Pytorch Implementation of Graph Convolutional Kernel Networks
  ☆54Updated 2 years ago
• karl-zhao / benchmarking-gnns-pyg
  ☆31Updated 2 years ago
• miafei / NodeNorm
  ☆30Updated 2 years ago
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 4 years ago
• ebonilla / VGCN
  Variational Graph Convolutional Networks
  ☆23Updated 4 years ago
• russchua / Graph-Isomorphism-Networks
  A Tensorflow 2.0 implementation of Graph Isomorphism Networks.
  ☆55Updated 6 years ago
• leowyy / GraphTSNE
  PyTorch Implementation of GraphTSNE, ICLR’19
  ☆136Updated 6 years ago
• leichen2018 / Ring-GNN
  ☆12Updated 5 years ago
• Nate1874 / StructPool
  The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields
  ☆58Updated 5 years ago
• lucfra / LDS-GNN
  Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)
  ☆197Updated last year