Despite growing interest in the use of complex models, such as machine learning (ML) models, for credit underwriting, ML models are difficult to interpret, and it is possible for them to learn ...

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 ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

A new analysis of the Hubble constant to show that the Gaussian Processes data reconstruction technique may not actually be independent of all cosmological models -- and that it may be time to ...

A machine-learning model trained on fewer than 300 molecules has flagged diatomic pairs with record-high electric dipole ...

Chemists may soon have one less rigorous step to worry about when searching for the right molecules to accomplish their ...

We propose an affine extension of the linear Gaussian term structure model (LGM) such that the instantaneous covariation of the factors is given by an affine process on semidefinite positive matrixes.