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

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

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 ...

Multi area RNN models fitted to in-vivo cortical activity predict behavioral changes induced by optogenetic perturbations, if biologically informed connectivity constraints on the optogenetically ...

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

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

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 ...

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

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