This catch is not specific to linear regression. It applies to any machine learning model in any domain — if the features available aren’t related to the phenomenon you’re trying to model ...

Density functional theory and the faster machine learning models trained on it, for example, can compute energy, forces, and thermodynamics. They lack spin degrees of freedom.

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, offering a more reliable and efficient alternative to traditional estimation ...

Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney Newey, James Robins, Double/debiased machine learning for treatment and structural parameters, The ...

As an example, look at GPT-3, a deep-learning model for natural languages that can generate text that is indistinguishable from text written by a person (yet can also go hilariously wrong).

Researchers have devised a new machine learning method to improve large-scale climate model projections and demonstrated that ...

A machine learning model was able to accurately predict peak and average intraocular pressure (IOP), according to a study published in Frontiers in Medicine. 1 This learning model could help with ...