Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

This study presents a transfer learning–based method for predicting train-induced environmental vibration. The method applies data fusion to combine physics-based numerical simulations and limited ...

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

With the power of Artificial Intelligence (AI), Google stepped up its game with another innovation. The company launched an experimental artificial intelligence weather model named Weather Lab to ...

de Filippis, R. and Al Foysal, A. (2026) Cross-Population Transfer Learning for Antidepressant Treatment Response Prediction: A SHAP-Based Explainability Approach Using Synthetic Multi-Ethnic Data.

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

Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development ...

Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...