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المنصة
الرئيسية
SOTA
تصنيف الرسم البياني
Graph Classification On Imdb M
Graph Classification On Imdb M
المقاييس
Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
Accuracy
Paper Title
U2GNN (Unsupervised)
89.2%
Universal Graph Transformer Self-Attention Networks
TFGW ADJ (L=2)
56.8%
Template based Graph Neural Network with Optimal Transport Distances
TREE-G
56.4%
TREE-G: Decision Trees Contesting Graph Neural Networks
MEWISPool
56.23%
Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks
DUGNN
56.10%
Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning
G_ResNet
54.53%
When Work Matters: Transforming Classical Network Structures to Graph CNN
sGIN
54.52%
Mutual Information Maximization in Graph Neural Networks
GIUNet
54%
Graph isomorphism UNet
U2GNN
53.60%
Universal Graph Transformer Self-Attention Networks
SEG-BERT
53.4%
Segmented Graph-Bert for Graph Instance Modeling
GIN-0
52.3%
How Powerful are Graph Neural Networks?
WEGL
52%
Wasserstein Embedding for Graph Learning
GFN
51.80%
Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification
1-WL Kernel
51.5%
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
DropGIN
51.4%
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks
GFN-light
51.20%
Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification
UGraphEmb-F
50.97%
Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity
Graph-JEPA
50.69%
Graph-level Representation Learning with Joint-Embedding Predictive Architectures
GMT
50.66%
Accurate Learning of Graph Representations with Graph Multiset Pooling
GDL
50.64%
Online Graph Dictionary Learning
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