Controllable Robustness Curve Prediction on SF networks
1.4Error RateCRL-SGNN
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| CRL-SGNNAverage degree <k>=10, RA condition=true2026.02 | 1.4 | 2 | |
| NCR-HoKAverage degree <k>=2, RA condition=true2026.02 | 1.6 | 1.2 | |
| PCRAverage degree <k>=2, RA condition=true2026.02 | 1.7 | 1.4 | |
| iPCRAverage degree <k>=2, RA condition=true2026.02 | 1.7 | 1.5 | |
| NCR-HoKAverage degree <k>=5, RA condition=true2026.02 | 1.9 | 1.5 | |
| NCR-HoKAverage degree <k>=Average, RA condition=true2026.02 | 1.9 | 1.5 | |
| PCRAverage degree <k>=5, RA condition=true2026.02 | 2 | 1.8 | |
| PCRAverage degree <k>=8, RA condition=true2026.02 | 2.1 | 2 | |
| PCRAverage degree <k>=Average, RA condition=true2026.02 | 2.1 | 1.9 | |
| NCR-HoKAverage degree <k>=8, RA condition=true2026.02 | 2.1 | 1.5 | |
| NCR-HoKAverage degree <k>=10, RA condition=true2026.02 | 2.1 | 1.6 | |
| CRL-SGNNAverage degree <k>=8, RA condition=true2026.02 | 2.2 | 1.8 | |
| CRL-SGNNAverage degree <k>=Average, RA condition=true2026.02 | 2.2 | 2.5 | |
| CRL-SGNNAverage degree <k>=2, RA condition=true2026.02 | 2.3 | 2.8 | |
| PCRAverage degree <k>=10, RA condition=true2026.02 | 2.4 | 2.2 | |
| CRL-SGNNAverage degree <k>=5, RA condition=true2026.02 | 2.7 | 3.4 | |
| iPCRAverage degree <k>=10, RA condition=true2026.02 | 4.2 | 5 | |
| iPCRAverage degree <k>=Average, RA condition=true2026.02 | 5.5 | 3.8 | |
| iPCRAverage degree <k>=8, RA condition=true2026.02 | 6.1 | 7.3 | |
| iPCRAverage degree <k>=5, RA condition=true2026.02 | 10 | 1.2 |