| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Filtering | Lorenz–63 | Average EW25.744 | 18 | |
| Filtering | Lorenz-96 10-dimensional | RMSE0.592 | 18 | |
| Time Series Forecasting | Lorenz Base | MSE1.34 | 17 | |
| Probabilistic Time Series Forecasting | Lorenz-Base H=192 | CRPS0.823 | 10 | |
| Probabilistic Time Series Forecasting | Lorenz-Base H=64 | CRPS0.295 | 10 | |
| Equation Discovery | Lorenz 96 Noise Levels: 0%, 1%, 10% (large) ODE | Mp1 | 8 | |
| Chaotic system forecasting | Lorenz-63 | VPT (0% noise)1.2 | 6 | |
| Time-series forecasting | Lorenz | Coverage@90%91 | 5 | |
| Time Series Forecasting | Lorenz | MSE21.82 | 4 | |
| Conservation-law discovery | lorenz (test) | F1 Score0 | 4 | |
| Vector Quantization | Lorenz | Act (%)99 | 4 | |
| Synthetic Dynamical System Modeling | Lorenz | Dynamics MSE0.141 | 4 | |
| Dynamics Modeling | Lorenz LO 1 single densely observed trajectory | Log Likelihood-0.57 | 3 | |
| Online adaptation recovery | Lorenz chaotic | Recovery Rate113 | 2 | |
| Learning Dynamical Systems | Lorenz | Relative L2 Error0.0453 | 2 | |
| Probabilistic Forecasting | Lorenz dataset (test) | RMSE2.91 | 2 | |
| Modeling Dynamical Systems | Lorenz '63 | Metric- | 0 | |
| Trajectory Prediction | Lorenz LO 125 (test) | Metric- | 0 |