Gaussian processes can be used as a supervised learning technique for classification as well as regression. An example of a classification task would be to recognize handwritten digits, whereas an example of a regression problem would be to learn the inverse dynamics of a robot arm (Fig. 1(a)). For the latter, the task is to obtain a mapping from the state of the arm (given by the positions, ve...

In these notes, we will talk about a different flavor of learning algorithms, known as Bayesian methods. Unlike classical learning algorithm, Bayesian algorithms do not attempt to identify “best-fit” models of the data (or similarly, make “best guess” predictions for new test inputs). Instead, they compute a posterior distribution over models (or similarly, compute posterior predictive distribu...

In these notes, we will talk about a different flavor of learning algorithms, known as Bayesian methods. Unlike classical learning algorithm, Bayesian algorithms do not attempt to identify “best-fit” models of the data (or similarly, make “best guess” predictions for new test inputs). Instead, they compute a posterior distribution over models (or similarly, compute posterior predictive distribu...