[
  {
    "Accuracy": 89.29,
    "code_links": [
      {
        "title": "tkipf/gae",
        "url": "https://github.com/tkipf/gae"
      },
      {
        "title": "Microsoft/gated-graph-neural-network-samples",
        "url": "https://github.com/Microsoft/gated-graph-neural-network-samples"
      },
      {
        "title": "tkipf/relational-gcn",
        "url": "https://github.com/tkipf/relational-gcn"
      },
      {
        "title": "MichSchli/RelationPrediction",
        "url": "https://github.com/MichSchli/RelationPrediction"
      },
      {
        "title": "INK-USC/RE-Net",
        "url": "https://github.com/INK-USC/RE-Net"
      },
      {
        "title": "INK-USC/RENet",
        "url": "https://github.com/INK-USC/RENet"
      },
      {
        "title": "INK-USC/MHGRN",
        "url": "https://github.com/INK-USC/MHGRN"
      },
      {
        "title": "masakicktashiro/rgcn_pytorch_implementation",
        "url": "https://github.com/masakicktashiro/rgcn_pytorch_implementation"
      },
      {
        "title": "chalothon/Graph-Convolutional-Networks-for-Relational-Link-Prediction",
        "url": "https://github.com/chalothon/Graph-Convolutional-Networks-for-Relational-Link-Prediction"
      },
      {
        "title": "susurrant/spatial-interaction-modeling",
        "url": "https://github.com/susurrant/spatial-interaction-modeling"
      },
      {
        "title": "susurrant/flow-imputation",
        "url": "https://github.com/susurrant/flow-imputation"
      }
    ],
    "date": "2017-03-17",
    "date2": 20170317,
    "model": "R-GCN",
    "paper": {
      "title": "Modeling Relational Data with Graph Convolutional Networks",
      "url": "https://cknow.io/lib/341fe850b7bc6d76"
    },
    "paper_data_uoa": "341fe850b7bc6d76"
  }
]