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Node Classification On Cora 1

Métriques

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
Accuracy
Paper TitleRepository
GCN-FP59.6%Convolutional Networks on Graphs for Learning Molecular Fingerprints
GGNN60.5%Gated Graph Sequence Neural Networks
MT-GCN73.1%Mutual Teaching for Graph Convolutional Networks
Snowball (tanh)74.78%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Snowball (linear)73.10%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Snowball (linear + tanh)74.79%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
AdaLanczosNet67.5 ± 8.7LanczosNet: Multi-Scale Deep Graph Convolutional Networks
LanczosNet66.1 ± 8.2LanczosNet: Multi-Scale Deep Graph Convolutional Networks
CPF-ind-APPNP80.24%Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework
VHCN78.1%View-Consistent Heterogeneous Network on Graphs With Few Labeled Nodes
ChebyNet44.2%Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Truncated Krylov78.15%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
GAT48.6%Graph Attention Networks
GraphSAGE49.0%Inductive Representation Learning on Large Graphs
DCNN66.4%Diffusion-Convolutional Neural Networks
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