KyotoU's team set out to develop a machine learning model integrated with neural networks. This new ensemble-learning method predicts the physical properties of unknown materials, using data based ...

But if you’re building predictive models with machine learning technology, it’s worth knowing that the addition of text analytics could be a force multiplier as you set out to leverage big data.

Academics from UK and China have developed a new machine learning algorithm that can break text-based CAPTCHA systems with less effort, faster, and with higher accuracy than all previous methods ...

This method is applied to a use case of water temperature prediction in the Delaware River Basin (DRB) and is designed to overcome some of the common pitfalls of prediction using machine learning ...

Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

Machine learning algorithms, especially decision-tree-based methods like random forest and LightGBM, significantly improved both prediction accuracy and computational efficiency.

Traditional methods, including commercial tools, require considerable time to produce accurate approximations, especially for complicated designs with numerous transistors. ML algorithms, on the other ...

The project I was a part of, Tectonic, was using machine learning to advance earthquake prediction. The European Research Council was sufficiently convinced of its potential to award it a four ...