Probabilistic ML – Lecture 11 – Example of GP Regression

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

* 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

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