CIN++-small
Reported on 3 benchmarks across 3 tasks · 1 paper
Note: results are matched by exact model name. Different papers may use the same name for different model variants.
Graphs2 results
- MAE· 2023-06-060.091best: 0.051 (ESA + rings + NodeRWSE + EdgeRWSE)
- ROC-AUC· 2023-06-0680.26best: 80.63 (CIN++)
Methodology1 result
- ROC-AUC· 2023-06-0680.26best: 80.63 (CIN++)