Continual Image Classification on CIFAR100 Split
85.4AccuracyIsolated tasks
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| Isolated tasks2023.06 | 85.4 | — | — | |
| n-GateONepsilon=02023.06 | 84.6 | — | — | |
| p-GateONepsilon=02023.06 | 82.5 | — | — | |
| RMN2023.06 | 80.1 | — | — | |
| Multitask2024.11 | 79.58 | — | — | |
| Multitask2025.09 | 79.58 | — | — | |
| CODE-CL2024.11 | 77.21 | -1.1 | — | |
| CODE-CL2025.09 | 77.21 | -1.1 | 33.8 | |
| SGP2025.09 | 76.05 | -1 | 22.27 | |
| SGP2024.11 | 75.69 | -1.4 | — | |
| CUBER2025.09 | 75.54 | 0.13 | 326.79 | |
| TRGP+SD2024.11 | 75.5 | -2.88 | — | |
| TRGP - SD2025.09 | 75.5 | -0.96 | — | |
| CUBER2024.11 | 75.3 | 0.1 | — | |
| EWC2023.06 | 75.3 | — | — | |
| TRGP2024.11 | 75.24 | -0.1 | — | |
| TRGP2025.09 | 74.64 | -0.9 | 78.86 | |
| DFGP2024.11 | 74.59 | -0.9 | — | |
| LMSP2025.09 | 74.21 | 0.94 | — | |
| GPM2025.09 | 72.48 | -0.9 | 22.27 | |
| HAT2024.11 | 72.06 | 0 | — | |
| GPM2024.11 | 72.06 | -0.2 | — | |
| HAT2025.09 | 72.06 | 0 | — | |
| ER_Res2024.11 | 71.73 | -6 | — | |
| ER_Res2025.09 | 71.73 | -6 | — | |
| LANCE2025.09 | 71.52 | -0.17 | 2.32 | |
| EWC2024.11 | 68.8 | -2 | — | |
| EWC2025.09 | 68.8 | -2 | — | |
| A-GEM2024.11 | 63.98 | -15 | — | |
| A-GEM2025.09 | 63.98 | -15 | — | |
| SSD+EWCK (active neurons)=10, Neurons per layer=100002025.12 | 52 | — | — | |
| OWM2024.11 | 50.94 | -30 | — | |
| SSDK (active neurons)=10, Neurons per layer=100002025.12 | 43 | — | — | |
| SDMLPK (active neurons)=10, Neurons per layer=100002025.12 | 32 | — | — | |
| EWCNeurons per layer=100002025.12 | 16 | — | — |