Node Classification On Citeseer 05

Metriken

Accuracy

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
MT-GCN	67.7%	Mutual Teaching for Graph Convolutional Networks
VCHN	65.6%	View-Consistent Heterogeneous Network on Graphs With Few Labeled Nodes
Truncated Krylov	64.64%	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
AdaLanczosNet	53.8 ± 4.7	LanczosNet: Multi-Scale Deep Graph Convolutional Networks
LanczosNet	53.2 ± 4.0	LanczosNet: Multi-Scale Deep Graph Convolutional Networks
DCNN	53.1%	Diffusion-Convolutional Neural Networks
ChebyNet	45.3%	Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
GGNN	44.3%	Gated Graph Convolutional Recurrent Neural Networks
GCN-FP	43.9%	Convolutional Networks on Graphs for Learning Molecular Fingerprints
GAT	38.2%	Graph Attention Networks
GraphSAGE	33.8%	Inductive Representation Learning on Large Graphs

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