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SOTA
Graph Classification
Graph Classification On Bbbp
Graph Classification On Bbbp
Metrics
ROC-AUC
Results
Performance results of various models on this benchmark
Columns
Model Name
ROC-AUC
Paper Title
G-Tuning
72.59
Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns
GTOT-Tuning
70
Fine-Tuning Graph Neural Networks via Graph Topology induced Optimal Transport
GMT
68.31
Accurate Learning of Graph Representations with Graph Multiset Pooling
0 of 3 row(s) selected.
Previous
Next
HyperAI
HyperAI
Home
Console
Docs
News
Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
Terms of Service
Privacy Policy
English
HyperAI
HyperAI
Toggle Sidebar
Search the site…
⌘
K
Command Palette
Search for a command to run...
Console
Home
SOTA
Graph Classification
Graph Classification On Bbbp
Graph Classification On Bbbp
Metrics
ROC-AUC
Results
Performance results of various models on this benchmark
Columns
Model Name
ROC-AUC
Paper Title
G-Tuning
72.59
Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns
GTOT-Tuning
70
Fine-Tuning Graph Neural Networks via Graph Topology induced Optimal Transport
GMT
68.31
Accurate Learning of Graph Representations with Graph Multiset Pooling
0 of 3 row(s) selected.
Previous
Next