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Node Classification On Cora 3

Metriken

Accuracy

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname
Accuracy
Paper TitleRepository
GraphSAGE64.2%Inductive Representation Learning on Large Graphs-
VCHN83.1%View-Consistent Heterogeneous Network on Graphs With Few Labeled Nodes
Truncated Krylov81.92%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks-
CPF-tra-GCNII84.18%Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework-
GCN-FP71.7%Convolutional Networks on Graphs for Learning Molecular Fingerprints-
MT-GCN78.5%Mutual Teaching for Graph Convolutional Networks-
GAT56.8%Graph Attention Networks-
AdaLanczosNet77.7 ± 2.4LanczosNet: Multi-Scale Deep Graph Convolutional Networks-
LanczosNet76.3 ± 2.3LanczosNet: Multi-Scale Deep Graph Convolutional Networks-
GGNN73.1%Gated Graph Sequence Neural Networks-
ChebyNet62.1%Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering-
Snowball (linear + tanh)79.52%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks-
Snowball (linear)80.96%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks-
Snowball (tanh)80.72%Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks-
DCNN76.7%Diffusion-Convolutional Neural Networks-
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Node Classification On Cora 3 | SOTA | HyperAI