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docs: enhance ReadTheDocs with visualization outputs and GitHub links

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Melvin Alvarez
2026-02-16 16:42:24 +01:00
parent 525015525b
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7 changed files with 64 additions and 13 deletions
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docs/source/api/optimal_control.md
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@@ -114,4 +114,4 @@ log_likelihoods = result.get_log_likelihoods()
**Conceptual picture:** Kalman filtering = prediction (dynamics prior) + correction (measurement residual). EKF linearizes $f, h$; UKF propagates sigma points for better nonlinear fidelity. RTS smoothing runs backward in time to refine all past states.
See `examples/notebooks/03_optimal_control_tutorial.ipynb` for end-to-end usage combining HJB thresholds, OU estimation, and filtering.
See [`examples/notebooks/03_optimal_control_tutorial.ipynb`](https://github.com/ThotDjehuty/optimiz-r/blob/main/examples/notebooks/03_optimal_control_tutorial.ipynb) for end-to-end usage combining HJB thresholds, OU estimation, and filtering.