paper-with-me

Node Classification 벤치마크

Node Classification on NELL

4개 결과 · ⬇ CSV · JSON

Accuracy

61.9 63.62 65.35 67.08 68.8 2016-03 2026-09 Planetoid* — 61.9 (2016-03-29) GCN — 66.0 (2016-09-09) GraphVAT — 64.7 (2019-02-20) DFNet-ATT — 68.8 (2019-10-24) Planetoid* — 61.9 (2016-03-29) GCN — 66.0 (2016-09-09) DFNet-ATT — 68.8 (2019-10-24)
RankModel Accuracy PaperCodeYear
1 DFNet-ATT 68.8 ± 0.3 DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters wokas36/DFNets 2019
2 GCN 66.0 Semi-Supervised Classification with Graph Convolutional Networks dmlc/dgl · dmlc/dgl · tkipf/gcn · +52 2016
3 GraphVAT 64.7% Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure fulifeng/GraphAT 2019
4 Planetoid* 61.9% Revisiting Semi-Supervised Learning with Graph Embeddings tkipf/gcn · kimiyoung/planetoid · DeepGraphLearning/GMNN · +23 2016
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