Gray-Scott
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| PDE solving | 2D Gray-Scott | Mean Error1.29 | 14 | |
| Forward (initial value problem) | Gray-Scott (test) | Relative MSE0.0512 | 12 | |
| Inverse (temporal conditioning) | Gray-Scott (test) | Relative MSE0.0253 | 12 | |
| PDE Solving | Gray-Scott long rollout | Relative L2 Error0.391 | 11 | |
| Dynamical system modeling | Gray-Scott (GS) m=3, n=1 (train) | MSE0 | 7 | |
| Operator Learning | Gray-Scott v (test) | Mean Relative L2 Error0.0579 | 5 | |
| Operator Learning | Gray-Scott (u) (test) | Mean Relative L2 Error0.01 | 5 | |
| Solving Partial Differential Equations | Gray-Scott | Total Parameters542,882 | 5 | |
| Partial Differential Equation Solving | Gray–Scott | Total Training Time (min)49.98 | 5 | |
| Operator Learning | Gray–Scott | Max GPU Memory Usage (GB)12.2 | 5 | |
| Operator Learning | 2D Gray-Scott | Relative L2 Error1.298 | 4 | |
| 2D Field Prediction | Gray-Scott 2D (test) | Mean RMSE0.0054 | 4 | |
| Continuum Dynamics Rollout Prediction | Gray-Scott T ∈ [21 : 60] | VRMSE0.1268 | 3 | |
| Continuum Dynamics Rollout Prediction | Gray-Scott | VRMSE2.78 | 3 | |
| 2D Operator Learning | 2D Gray-Scott | Mean RMSE0.0054 | 2 | |
| Temporal interpolation | Gray-Scott (test) | Relative MSE0.0178 | 2 | |
| Dynamical system modeling | Gray-Scott (GS) m=3, n=1 (test) | Metric- | 0 |
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