[
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    "10%": 60.6,
    "code_links": [
      {
        "title": "ser-art/RAE-vs-AE",
        "url": "https://github.com/ser-art/RAE-vs-AE"
      }
    ],
    "date": "2018-02-09",
    "date2": 20180209,
    "model": "DR^2N",
    "paper": {
      "title": "Relational Autoencoder for Feature Extraction",
      "url": "https://cknow.io/lib/0493589ea3972712"
    },
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  },
  {
    "10%": 58.1,
    "code_links": [
      {
        "title": "PetarV-/GAT",
        "url": "https://github.com/PetarV-/GAT"
      },
      {
        "title": "Diego999/pyGAT",
        "url": "https://github.com/Diego999/pyGAT"
      },
      {
        "title": "danielegrattarola/keras-gat",
        "url": "https://github.com/danielegrattarola/keras-gat"
      },
      {
        "title": "shenweichen/GraphNeuralNetwork",
        "url": "https://github.com/shenweichen/GraphNeuralNetwork"
      },
      {
        "title": "HazyResearch/hgcn",
        "url": "https://github.com/HazyResearch/hgcn"
      },
      {
        "title": "GraphSAINT/GraphSAINT",
        "url": "https://github.com/GraphSAINT/GraphSAINT"
      },
      {
        "title": "ds4dm/sGat",
        "url": "https://github.com/ds4dm/sGat"
      },
      {
        "title": "ds4dm/sparse-gcn",
        "url": "https://github.com/ds4dm/sparse-gcn"
      },
      {
        "title": "snowkylin/gnn",
        "url": "https://github.com/snowkylin/gnn"
      },
      {
        "title": "HeapHop30/graph-attention-nets",
        "url": "https://github.com/HeapHop30/graph-attention-nets"
      },
      {
        "title": "zhao-tong/GNNs-easy-to-use",
        "url": "https://github.com/zhao-tong/GNNs-easy-to-use"
      },
      {
        "title": "weiyangfb/PyTorchSparseGAT",
        "url": "https://github.com/weiyangfb/PyTorchSparseGAT"
      },
      {
        "title": "Yindong-Zhang/myGAT",
        "url": "https://github.com/Yindong-Zhang/myGAT"
      },
      {
        "title": "marble0117/GNN_models_pytorch",
        "url": "https://github.com/marble0117/GNN_models_pytorch"
      },
      {
        "title": "marble0117/GNN_models_pytorch_geometric",
        "url": "https://github.com/marble0117/GNN_models_pytorch_geometric"
      },
      {
        "title": "calciver/Graph-Attention-Networks",
        "url": "https://github.com/calciver/Graph-Attention-Networks"
      },
      {
        "title": "fongyk/graph-attention",
        "url": "https://github.com/fongyk/graph-attention"
      },
      {
        "title": "handasontam/GAT-with-edgewise-attention",
        "url": "https://github.com/handasontam/GAT-with-edgewise-attention"
      },
      {
        "title": "BIG-S2/keras-gnm",
        "url": "https://github.com/BIG-S2/keras-gnm"
      },
      {
        "title": "ColdenChan/GAT_D",
        "url": "https://github.com/ColdenChan/GAT_D"
      },
      {
        "title": "YunseobShin/wiki_GAT",
        "url": "https://github.com/YunseobShin/wiki_GAT"
      },
      {
        "title": "mlzxzhou/keras-gnm",
        "url": "https://github.com/mlzxzhou/keras-gnm"
      },
      {
        "title": "Anak2016/GAT",
        "url": "https://github.com/Anak2016/GAT"
      },
      {
        "title": "snownus/COOP",
        "url": "https://github.com/snownus/COOP"
      },
      {
        "title": "subercui/pyGConvAT",
        "url": "https://github.com/subercui/pyGConvAT"
      },
      {
        "title": "ChengSashankh/trying-GAT",
        "url": "https://github.com/ChengSashankh/trying-GAT"
      },
      {
        "title": "mitya8128/experiments_notes",
        "url": "https://github.com/mitya8128/experiments_notes"
      }
    ],
    "date": "2017-10-30",
    "date2": 20171030,
    "model": "GAT",
    "paper": {
      "title": "Graph Attention Networks",
      "url": "https://cknow.io/lib/42fabb81d929f34c"
    },
    "paper_data_uoa": "42fabb81d929f34c"
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]