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Node Classification On Pubmed 01

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Model Name
Accuracy
Paper TitleRepository
Truncated Krylov77.21%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks-
DCNN73.1%Diffusion-Convolutional Neural Networks-
GAT59.6%Graph Attention Networks-
GCN-FP70.3%Convolutional Networks on Graphs for Learning Molecular Fingerprints-
GGNN70.4%Gated Graph Sequence Neural Networks-
ChebyNet55.2%Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering-
LanczosNet73.4 ± 5.1LanczosNet: Multi-Scale Deep Graph Convolutional Networks-
Snowball (linear + tanh)75.30%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks-
VCHN76.8%View-Consistent Heterogeneous Network on Graphs With Few Labeled Nodes
GraphSAGE65.4%Inductive Representation Learning on Large Graphs-
AdaLanczosNet72.8 ± 4.6LanczosNet: Multi-Scale Deep Graph Convolutional Networks-
Snowball (tanh)74.40%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks-
MT-GCN73.1%Mutual Teaching for Graph Convolutional Networks-
Snowball (linear)73.83%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks-
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Node Classification On Pubmed 01 | SOTA | HyperAI