• DropEdge

  • Referenced in 3 articles [sw37753]
  • Node Classification. Over-fitting and over-smoothing are two main obstacles of developing deep Graph ... generalization ability on small dataset, while over-smoothing impedes model training by isolating output representations ... either reduces the convergence speed of over-smoothing or relieves the information loss caused ... effect of DropEdge on preventing over-smoothing is empirically visualized and validated as well. Codes...
  • PyTorch

  • Referenced in 390 articles [sw20939]
  • PyTorch python package: Tensors and Dynamic neural networks...
  • DGL

  • Referenced in 11 articles [sw33907]
  • Deep Graph Library: A Graph-Centric, Highly-Performant...
  • GraphSAGE

  • Referenced in 4 articles [sw33908]
  • GraphSAGE is a framework for inductive representation learning...
  • FastGCN

  • Referenced in 7 articles [sw38089]
  • FastGCN: Fast Learning with Graph Convolutional Networks via...
  • CayleyNets

  • Referenced in 5 articles [sw38090]
  • CayleyNets: Graph Convolutional Neural Networks with Complex Rational...