Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even ...

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...

The model based on Gaussian process (GP) prior and a kernel covariance function can be used to fit nonlinear data with multidimensional covariates. It has been used as a flexible nonparametric ...

Pantelis Samartsidis, Claudia R. Eickhoff, Simon B. Eickhoff, Tor D. Wager, Lisa Feldman Barrett, Shir Atzil, Timothy D. Johnson, Thomas E. Nichols, Bayesian log-Gaussian Cox process regression, ...

A good way to see where this article is headed is to take a look at the screenshot in Figure 1. The demo program loads a 200-item set of training data and a 40-item set of test data into memory. The ...