benchmark datasets
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Time Series Classification | benchmark datasets 30% Missing (test) | Accuracy75 | 25 | |
| Time Series Classification | 30 benchmark datasets Regular (test) | Accuracy76.7 | 25 | |
| Anomaly Detection | 34 benchmark datasets aggregate (test) | Cost per Example0.113 | 20 | |
| Continual Learning Evaluation | Six Benchmark Datasets Overall | Average Accuracy73.3 | 19 | |
| Outlier Detection | 39 Benchmark Datasets | p-value0 | 18 | |
| Quantile Regression | 122 benchmark datasets | Normalized Quantile Loss0.015 | 10 | |
| Base-to-new generalization | Average of 10 benchmark datasets | Base Accuracy81.31 | 10 | |
| Imbalanced Classification | 27 benchmark datasets | MD Metric75.7 | 8 | |
| Classification | 19 benchmark datasets | Max ALL-RRS Score81.5 | 7 | |
| Time Series Classification | 30 benchmark datasets Pairwise Comparison (test) | Win Count (vs Neural ODE, TANDEM)114 | 4 | |
| Drug Synergy Prediction | Benchmark Datasets | Tau (Train, 100)15.41 | 4 | |
| Time Series Classification | 30 benchmark datasets 70% Missing (test) | Accuracy70.9 | 2 | |
| Time Series Classification | 30 benchmark datasets All settings (test) | Accuracy74.2 | 1 | |
| Anomaly Detection | 119 benchmark datasets | Metric- | 0 | |
| End-to-end detection and explanation | 7 Benchmark Datasets | Metric- | 0 |
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