## A visual exploration of Gaussian Processes and Infinite Neural Networks

** Published:**

Gaussian Processes (GPs) generalize Gaussian distributions to random variables that are functions (stochastic processes). As such, they are a powerful tool for regression and Bayesian inference. In the past years, they have received increased attention due to the interest in machine learning. An intriguing connection between GPs and neural network exists when the width of layers in feed-forward neural networks tends towards infinity. For a specific choice of the prior distributions that governs the network parameters, the resulting network will be a GP.