Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

Researchers from China University of Petroleum (East China), in collaboration with international partners, have reported a ...

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 ...

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...

A team led by Guoyin Yin at Wuhan University and the Shanghai Artificial Intelligence Laboratory recently proposed a modular machine learning ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...

Relating brain activity to behavior is an ongoing aim of neuroimaging research as it would help scientists understand how the brain begets behavior — and perhaps open new opportunities for ...

The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...