| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Tabular Anomaly Detection | Ionosphere | AUC-ROC99.21 | 50 | |
| Classification | Ionosphere | PR AUC97.5 | 24 | |
| Outlier Detection | Ionosphere | AP90.4 | 22 | |
| Anomaly Detection | Ionosphere | AUC-ROC99.86 | 17 | |
| Anomaly Detection | Ionosphere | AUC-PR98.95 | 17 | |
| Classification | Ionosphere UCIrvine (5-fold cross-validation) | Macro F1 Score97.14 | 17 | |
| Classification | Ionosphere 20% | PR AUC97.2 | 12 | |
| Classification | ionosphere (test) | Loss0.2648 | 11 | |
| Classification | Ionosphere | Log Time (s)0.31 | 11 | |
| Outlier Detection | Ionosphere | AUC0.915 | 11 | |
| Anomaly Detection | ionosphere Out-of-Domain | F1 Score93.49 | 10 | |
| Classification | Ionosphere | Avg. Accuracy0.942 | 10 | |
| Classification | ionosphere | Average Test Accuracy94 | 10 | |
| Outlier Detection | Ionosphere | Precision-s84.79 | 9 | |
| Continual Clustering | Ionosphere | AI NMI62.4 | 9 | |
| Classification | Ionosphere UCIrvine | Macro F197.6 | 9 | |
| Classification | ionosphere | Improvement in Balanced Accuracy0.015 | 8 | |
| Data Synthesis | ionosphere | MMD0.08 | 8 | |
| Active Learning | Ionosphere | AULC81 | 8 | |
| Classification | Ionosphere | ROC AUC98.7 | 8 | |
| Tabular Classification | Ionosphere | Cohen's Kappa0.888 | 8 | |
| Classification | Ionosphere | F1-Macro98.5 | 8 | |
| Counterfactual Explanation | ionosphere | Validity1 | 8 | |
| Bayesian logistic regression | Ionosphere (d=61) | Avg Posterior Log-Likelihood-205.49 | 7 | |
| Outlier Detection | ionosphere (full) | Recall49.83 | 7 |