HyperAI
الرئيسيةالأخبارأحدث الأوراق البحثيةالدروسمجموعات البياناتالموسوعةSOTAنماذج LLMلوحة الأداء GPUالفعاليات
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HyperAI

Node Classification On Citeseer 05

المقاييس

Accuracy

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

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