AD
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Medical Image Classification | AD | Accuracy79.12 | 26 | |
| Tabular Classification | AD | Accuracy85.4 | 16 | |
| Utility evaluation | AD | Balanced Accuracy81.8 | 13 | |
| Minority class representation | AD | Minority Class Percentage26.3 | 13 | |
| DCR baseline protection analysis | AD | DCR Baseline Protection0.321 | 12 | |
| Membership Inference Attack | AD | Success Rate51.3 | 12 | |
| Synthetic Data Evaluation (Column Pair Trends) | AD | Column Pair Trends Score0.916 | 12 | |
| Overfitting Protection Evaluation | AD | DCR Overfitting Protection0.901 | 12 | |
| Tabular Synthetic Data Generation | AD | Column Shapes Score0.972 | 12 | |
| Re-ranking | Ad (test) | MAP@561.55 | 10 | |
| SID Quality | Ad-60W | V-Measure71.32 | 9 | |
| Sequential Recommendation | AD (test) | Recall@10.69 | 8 | |
| Classification | AD | Accuracy87.4 | 8 | |
| EEG Classification | AD 1% labels (test) | Accuracy88.22 | 7 | |
| EEG Classification | AD 10% labels (test) | Accuracy91.43 | 7 | |
| EEG Classification | AD 100% labels (test) | Accuracy84.5 | 7 | |
| Tabular Classification | AD | Macro F181.5 | 6 | |
| Anomaly Detection | AD unbalanced (test) | Accuracy88.22 | 6 | |
| Tabular Classification | AD (test) | AUROC0.91 | 4 | |
| Synthetic Tabular Data Generation | AD | DCR101 | 4 | |
| Density Estimation | Ad Twenty Datasets (test) | Log-LH-28.58 | 4 | |
| Accuracy Estimation | AD-10 (test) | AUPR0.8935 | 4 | |
| Next-ad prediction | Ad-100W | HR@14.49 | 3 | |
| Clustering | AD dataset | Silhouette Score0.1381 | 3 | |
| Density Estimation | ad discrete (test) | Log-Likelihood-16.07 | 3 |
Showing 25 of 26 rows