COVID-19
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Equilibrium State Estimation | COVID-19 | Computational Cost (20 Regions)0.18 | 132 | |
| Time-series Forecasting | COVID-19 20 regions | RMSE15.86 | 104 | |
| Multi-step short-term forecasting | COVID-19 (test) | MAE0.071 | 58 | |
| Equilibrium State Estimation | COVID-19 (79 regions) | RMSE50.99 | 29 | |
| Multivariate Time Series Forecasting | COVID-19 (test) | MAE0.071 | 28 | |
| Time-series forecasting | COVID-19 Input Length 100 (test) | RMSE (20 regions)80.67 | 26 | |
| Time-series forecasting | COVID-19 Input Length 50 (test) | RMSE (20 regions)59.12 | 26 | |
| Time-series forecasting | COVID-19 Input Length 20 (test) | RMSE (20 regions)49.79 | 26 | |
| Time-series forecasting | COVID-19 Input Length 10 (test) | RMSE (20 regions)20.48 | 26 | |
| State Estimation | COVID-19 320 Suburbs | RMSE4.36 | 26 | |
| State Estimation | COVID-19 20 Regions | RMSE70.01 | 26 | |
| Short-term forecasting | COVID-19 | MAE0.123 | 26 | |
| Time-series Forecasting | COVID-19 79 regions | RMSE51.31 | 24 | |
| Equilibrium State Estimation | COVID-19 (test) | RMSE (20 regions)16.41 | 24 | |
| Policy Selection | COVID-19 | Precision@383.3 | 24 | |
| Epidemic Forecasting | COVID-19 (Overall) | RMSE169.1 | 23 | |
| Epidemic Forecasting | COVID-19 (14 d Ahead) | RMSE230.1 | 23 | |
| Epidemic Forecasting | COVID-19 7 d Ahead | RMSE149.3 | 23 | |
| Epidemic Forecasting | COVID-19 3 d Ahead | RMSE125.3 | 23 | |
| Multivariate Time Series Forecasting | COVID-19 | MAE0.123 | 23 | |
| Medical Image Segmentation | Covid-19 | Dice Score45.04 | 21 | |
| Medical Image Classification | Covid-19 | F1-Score97.78 | 20 | |
| Opinion Dynamics Modeling | COVID-19 (60 T) | RMSE20.05 | 17 | |
| Opinion Dynamics Modeling | COVID-19 (30 T) | RMSE18.26 | 17 | |
| Out-of-Distribution Detection | COVID-19 (clean) | Accuracy99 | 16 |
Showing 25 of 86 rows