| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| Fashion-MNIST | f-FUM (KL-KL) | Pre-training Accuracy65.93 | 20 | 4d ago | |
| CIFAR-10 | f-FUM (KL-KL) | Pretrain Accuracy68.7 | 20 | 4d ago | |
| MNIST (test) | Ours (KL-KL) | Pretrain Accuracy99.13 | 20 | 4d ago | |
| Fashion-MNIST (test) | Ours (KL-KL) | Pre-training Accuracy99.2 | 20 | 4d ago | |
| CIFAR-10 (test) | Ours (KL-KL) | Pretrain Accuracy80 | 20 | 4d ago | |
| CIFAR-10 (Retain) | Accuracy100 | 14 | 4d ago | ||
| Fashion-MNIST | Ours (KL-KL) | Pre-training Accuracy81.58 | 12 | 4d ago | |
| MNIST | Ours (KL-KL) | Accuracy (Pretrain)0.9914 | 12 | 4d ago | |
| CIFAR-10 | Ours (KL-KL) | Pretrain Accuracy79.72 | 12 | 4d ago | |
| Fashion-MNIST (val) | f-FUM (KL-KL) | Pretrain Accuracy73.85 | 12 | 4d ago | |
| MNIST (val) | f-FUM (KL-KL) | Pretrain Acc99.14 | 12 | 4d ago | |
| CIFAR-10 (val) | f-FUM (KL-KL) | Pretrain Accuracy63.64 | 12 | 4d ago | |
| MNIST | f-FUM (KL-KL) | Pretraining Accuracy93.49 | 10 | 4d ago | |
| Fashion-MNIST MINILENET | f-FUM (KL-KL) | Pretrain Accuracy49.07 | 10 | 4d ago | |
| CIFAR-10 ResNet-18 | f-FUM (KL-KL) | Pretrain Accuracy58.54 | 10 | 4d ago | |
| Caltech-101 standard (All) | Average Gap0 | 6 | 4d ago | ||
| Tiny-ImageNet | GA | Unlearning Runtime (s)22.33 | 5 | 3d ago | |
| CIFAR-100 | GA | Running Time (sec)4.14 | 5 | 3d ago | |
| CIFAR-10 | GA | Running Time (sec)1.85 | 5 | 3d ago | |
| MedMNIST | GA | Running time (sec)1.3 | 5 | 3d ago | |
| Income | GA | Running Time (s)0.79 | 5 | 3d ago | |
| CIFAR-10 (Forget) | Accuracy87.66 | 5 | 4d ago | ||
| CIFAR-10 | F-Acc0 | 5 | 4d ago | ||
| CIFAR-100 (Retain) | Accuracy99.96 | 4 | 4d ago | ||
| Caltech-101 (Forget) | NoT | Accuracy50.81 | 2 | 4d ago |
