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# ssm-book
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-Interactive textbook on state-space models.
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+Executable textbook on state-space models, to accompany the [dynamax](https://github.com/probml/dynamax) library.
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The rendered content can be found at [https://probml.github.io/ssm-book/root.html](https://probml.github.io/ssm-book/root.html).
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+Authors: Kevin Murphy, Scott Linderman, et al. MIT License. 2022
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+Related books:
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+- [Probabilistic Machine Learning: Advanced Topics](https://probml.github.io/pml-book/book2.html). Kevin Murphy, 2023. See chapters 8, 9 and 29.
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+[JAX code](https://probml.github.io/dynamax/)
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+- [Bayesian filtering and smoothing](https://users.aalto.fi/~ssarkka/pub/cup_book_online_20131111.pdf), Simo Sarkka, 2013. [Matlab code](https://www.cambridge.org/us/academic/subjects/statistics-probability/applied-probability-and-stochastic-networks/bayesian-filtering-and-smoothing?format=HB), [Numpy code](https://github.com/EEA-sensors/Bayesian-Filtering-and-Smoothing/tree/main/python), [Jax code](https://github.com/petergchang/sarkka-jax)
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+- [State estimation for robotics](http://asrl.utias.utoronto.ca/~tdb/bib/barfoot_ser17.pdf), Tim Barfoot, 2017.
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+- [Kalman and Bayesian filters in Python](https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python), Roger Labbe, 2015. [Python code](https://github.com/rlabbe/filterpy)
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Kevin P Murphy