# ssm-book

**Repository Path**: sshidy/ssm-book

## Basic Information

- **Project Name**: ssm-book
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-05-27
- **Last Updated**: 2024-05-27

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# ssm-book
Executable textbook on state-space models, to accompany the [dynamax](https://github.com/probml/dynamax) library.
The rendered content can be found at [https://probml.github.io/ssm-book/root.html](https://probml.github.io/ssm-book/root.html).



Authors: Kevin Murphy, Scott Linderman, et al. MIT License. 2022



Related books:
- [Probabilistic Machine Learning: Advanced Topics](https://probml.github.io/pml-book/book2.html). Kevin Murphy, 2023. See chapters 8, 9 and 29.
[JAX code](https://probml.github.io/dynamax/)
- [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)
- [State estimation for robotics](http://asrl.utias.utoronto.ca/~tdb/bib/barfoot_ser17.pdf), Tim Barfoot, 2017.
- [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)