State Reconstruction on 12 different tasks Correlated Gaussian noise
0.0114Geometric Mean State MSEMAAT
Evaluation Results
| Method | Links | |
|---|---|---|
| MAATDownstream Symbolic Regression=SINDy2026.01 | 0.0114 | |
| MAATDownstream Symbolic Regression=PySR2026.01 | 0.0141 | |
| Gaussian Process (RBF)Downstream Symbolic Regression=PySR2026.01 | 0.0186 | |
| PINNDownstream Symbolic Regression=PySR2026.01 | 0.0247 | |
| Gaussian Process (RBF)Downstream Symbolic Regression=SINDy2026.01 | 0.0256 | |
| PINNDownstream Symbolic Regression=SINDy2026.01 | 0.0355 | |
| Kalman filter / RTSDownstream Symbolic Regression=PySR2026.01 | 0.0852 | |
| Kalman filter / RTSDownstream Symbolic Regression=SINDy2026.01 | 0.0883 | |
| Savitzky–GolayDownstream Symbolic Regression=SINDy2026.01 | 0.119 | |
| TVRegDiffDownstream Symbolic Regression=SINDy2026.01 | 0.119 | |
| TVRegDiffDownstream Symbolic Regression=PySR2026.01 | 0.121 | |
| Savitzky–GolayDownstream Symbolic Regression=PySR2026.01 | 0.127 | |
| Linear interpolationDownstream Symbolic Regression=SINDy2026.01 | 0.212 | |
| Linear interpolationDownstream Symbolic Regression=PySR2026.01 | 0.222 | |
| RBF interpolationDownstream Symbolic Regression=SINDy2026.01 | 0.328 | |
| RBF interpolationDownstream Symbolic Regression=PySR2026.01 | 0.4 | |
| Cubic splineDownstream Symbolic Regression=SINDy2026.01 | 0.42 | |
| Cubic splineDownstream Symbolic Regression=PySR2026.01 | 0.465 | |
| Neural ODEDownstream Symbolic Regression=SINDy2026.01 | 0.837 | |
| Neural ODEDownstream Symbolic Regression=PySR2026.01 | 5.65 |