Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent sintering under high temperatures. Metal nanoparticles catalyze reactions ...

The findings show that boosting algorithms, a class of machine learning models, consistently outperform traditional statistical methods, particularly for traits with well-defined genetic signals. In ...

This guest essay reflects the views of Nirali Somia, a graduate student at Cold Spring Harbor Laboratory. It is part of a series of essays from current researchers at the Cold Spring Harbor Laboratory ...

A team has proposed an interpretable machine learning approach that predicts print time and filament use for FFF, potentially ...

The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...

Mentalising brain signatures reveal distinct self/other neural patterns from adolescence and are altered in schizophrenia, suggesting candidate neuromarkers.

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...

Work you complete in the non-credit experience will transfer to the for-credit experience when you upgrade and pay tuition. See How It Works for details. A previous version of Machine Learning: Theory ...