Traditional time-series forecasting models are ill-equipped to handle the dynamic and event- driven nature of Q-commerce ...

If you work with data, or data people, you’ve probably heard the saying “garbage in, garbage out.” It’s shorthand for what ...

A new machine learning tool by Trugard and Webacy targets crypto wallet address poisoning, with the companies reporting 97% ...

In a recent analysis, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and collaborator William Gilpin reported that one ...

A research team from Kumamoto University has developed a promising deep learning model that significantly enhances the ...

Postpartum depression (PPD) affects up to 15% of individuals after childbirth. Early identification of patients at risk of ...

As web applications become more sophisticated to meet our daily needs, such as shopping and communication, they also become more vulnerable to data breaches. In 2024, web applications were the ...

Here, we developed interpretable machine learning models that can classify uranium minerals by secondary oxyanion chemistry and other physicochemical properties based solely on Raman spectra. This new ...

matching targeted mechanical responses within one to 15 percent accuracy, which were experimentally validated,” Espinosa said. Most approaches to machine learning-based inverse design require large ...