| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | Fashion MNIST (test) | Accuracy96.35 | 568 | |
| Image Classification | Fashion MNIST | Accuracy96.91 | 225 | |
| Clustering | Fashion-MNIST | NMI80 | 95 | |
| Anomaly Detection | Fashion-MNIST | Avg AUC95.6 | 40 | |
| Image Generation | Fashion-MNIST | FID1.49 | 38 | |
| Image Classification | Fashion-MNIST (val) | Accuracy95.56 | 37 | |
| VAE Log-Likelihood Estimation | Fashion MNIST (test) | Log-Likelihood-233.39 | 30 | |
| Generative Modeling | Fashion MNIST (train) | Log Likelihood (100 samples)-230.77 | 30 | |
| kNN Classification | Fashion-MNIST | Accuracy81.8 | 30 | |
| Federated Learning Fairness | Fashion MNIST (test) | Accuracy Variance1.005 | 28 | |
| Deep Clustering | Fashion-MNIST (test) | SC0.922 | 28 | |
| Image Classification | Fashion-MNIST Dir(0.5) (test) | Accuracy90.49 | 28 | |
| Image Classification | Fashion-MNIST under sudden drift and Dir(0.1) 1.0 (test) | Accuracy (Generalized)87.63 | 28 | |
| Image Classification | Fashion-MNIST Dir(0.5) | Accuracy90.57 | 28 | |
| Classification | Fashion MNIST | AUC89.6 | 25 | |
| Stimulus Encoding | Fashion-MNIST | SSIM97 | 24 | |
| Image Classification | Rotated Fashion MNIST (target domains 0° and 90°) | Accuracy81.6 | 21 | |
| Federated Unlearning | Fashion-MNIST | Pre-training Accuracy65.93 | 20 | |
| Federated Unlearning | Fashion-MNIST (test) | Pre-training Accuracy99.2 | 20 | |
| Federated Image Classification | Fashion-MNIST (test) | Accuracy82.4 | 20 | |
| Image Classification | Fashion-MNIST standard (test) | Accuracy96.3 | 18 | |
| Deep Clustering | Fashion-MNIST | Execution Time (s)732 | 18 | |
| Clustering | Fashion-MNIST standard (test) | ARI65.8 | 17 | |
| Image Classification | Fashion-MNIST (train) | Accuracy (Train)100 | 17 | |
| Image Classification | Fashion-MNIST | Accuracy96.1 | 16 |