Kalman smoothing as forward-backward
(40 minutes to learn)
Kalman smoothing can be seen as a special case of the forward-backward algorithm for inference in HMMs. This leads to a simpler derivation than the classical one.
This concept has the prerequisites:
Core resources (read/watch one of the following)
→ Pattern Recognition and Machine Learning
A textbook for a graduate machine learning course, with a focus on Bayesian methods.
Location: Section 13.3.1, pages 638-641
Supplemental resources (the following are optional, but you may find them useful)
→ Machine Learning: a Probabilistic Perspective
A very comprehensive graudate-level machine learning textbook.
Location: Section 18.104.22.168, pages 645-646
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