Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...

A study in Nature Communications by Michele Ceriotti’s group at EPFL has introduced a new dataset and model that greatly improve the efficiency of machine-learning interatomic potentials (MLIPs) and ...

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...