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Node Classification On Citeseer 05

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Paper Title
MT-GCN67.7%Mutual Teaching for Graph Convolutional Networks
VCHN65.6%View-Consistent Heterogeneous Network on Graphs With Few Labeled Nodes
Truncated Krylov64.64%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Snowball (tanh)62.05%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Snowball (linear + tanh)61.99%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Snowball (linear)59.41%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
AdaLanczosNet53.8 ± 4.7LanczosNet: Multi-Scale Deep Graph Convolutional Networks
LanczosNet53.2 ± 4.0LanczosNet: Multi-Scale Deep Graph Convolutional Networks
DCNN53.1%Diffusion-Convolutional Neural Networks
ChebyNet45.3%Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
GGNN44.3%Gated Graph Convolutional Recurrent Neural Networks
GCN-FP43.9%Convolutional Networks on Graphs for Learning Molecular Fingerprints
GAT38.2%Graph Attention Networks
GraphSAGE33.8%Inductive Representation Learning on Large Graphs
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Node Classification On Citeseer 05 | SOTA | HyperAI