Probabilistic ML - 10 - Time Series and Markov Chains

This is Lecture 10 of the course on Probabilistic Machine Learning in the Summer Term of 2025 at the University of Tübingen, taught by Prof. Philipp Hennig. Contents include a theoretical derivation of the Bayesian Filtering and Smoothing equations from first principles, and a discussion of the resulting associative prefix-sum structure. Probabilistic ML is an integral part of the curriculum of the International Masters Degree in Machine Learning, alongside associated courses on deep learning, statistical machine learning, reinforcement learning, and much more. Playlist for the course:    • Probabilistic Machine Learning 2025 - Phil...