Energy
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Tabular Data Synthesis Fidelity | energy | KS Distance0.62 | 42 | |
| Regression | Energy UCI (test) | RMSE0.441 | 27 | |
| Tabular Data Synthesis | energy | Inverse KL0.12 | 21 | |
| Tabular Data Synthesis | energy | Chi-squared Test Result0.03 | 21 | |
| Time-series Generation | Energy | Discriminative Score0.553 | 21 | |
| Classification | energy | Balanced Accuracy35.74 | 20 | |
| Time Series Forecasting | Energy | MSE0.079 | 16 | |
| Regression | Energy 100% non-corrupted features | RMSE0.08 | 15 | |
| Regression | Energy 50% non-corrupted features | RMSE0.082 | 15 | |
| Regression | Energy 0% non-corrupted features | RMSE0.089 | 15 | |
| Regression | Energy | RMSE0.112 | 13 | |
| Regression | energy 19735x26 | Mean MSE210.28 | 11 | |
| Regression | Energy | Min Epsilon0.0496 | 9 | |
| Regression | energy CV (test) | R20.93 | 8 | |
| Regression | Energy (test) | RMSE3.74 | 8 | |
| Regression | Energy OOD rescaled by 0.1 non-normalized UCI (test) | RMSE9.5 | 8 | |
| Regression | Energy | Relative Percentage Error1 | 8 | |
| Irregular-to-regular Time Series Generation | Energy 70% missing | DS0.497 | 8 | |
| Irregular-to-regular Time Series Generation | Energy (50% missing) | DS0.487 | 8 | |
| Irregular-to-regular Time Series Generation | Energy 30% missing | DS0.422 | 8 | |
| Regression | Energy | Avg NLL Relative Percentage0 | 8 | |
| Regression | Energy 5-fold CV | RMSE67.97 | 7 | |
| Regression | Energy UCI rescaled 3x std normalized (test) | RMSE5.28 | 7 | |
| Regression | Energy (3 train-test splits) | LPPD2.204 | 7 | |
| Continuous Time Series Generation | Energy 70% missing | MSE0.013 | 6 |
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