Node Classification On Pubmed 005

Metriken

Accuracy

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
VCHN	74.3%	View-Consistent Heterogeneous Network on Graphs With Few Labeled Nodes
Truncated Krylov	72.57%	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Snowball (linear)	70.04%	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
MT-GCN	69.5%	Mutual Teaching for Graph Convolutional Networks
Snowball (linear + tanh)	69.45%	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Snowball (tanh)	68.99%	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
LanczosNet	68.8 ± 5.6	LanczosNet: Multi-Scale Deep Graph Convolutional Networks
DCNN	66.7%	Diffusion-Convolutional Neural Networks
AdaLanczosNet	66%	LanczosNet: Multi-Scale Deep Graph Convolutional Networks
GGNN	63.3%	Gated Graph Sequence Neural Networks
GCN-FP	63.2%	Convolutional Networks on Graphs for Learning Molecular Fingerprints
GraphSAGE	53.0%	Inductive Representation Learning on Large Graphs
GAT	50.4%	Graph Attention Networks
ChebyNet	48.2%	Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

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Node Classification On Pubmed 005 | SOTA | HyperAI