This is the eleventh lecture in the Probabilistic ML class of Prof. Dr. Philipp Hennig in the Summer Term 2020 at the University of Tübingen.
Time-stamped slides available at https://uni-tuebingen.de/en/180804.
Contents:
* A concrete example of Gaussian process regression
* Kernel design
* Feature design
* Source Separation
* Additive Models
* Hierarchical Bayesian Inference
© Philipp Hennig / University of Tübingen, 2020 CC BY-NC-SA 3.0