Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

White paper discusses how BullFrog AI’s bfPREP™ embodies data harmonization, enabling biopharma organizations to convert noisy, document-heavy data into standardized, AI-ready datasetsGAITHERSBURG, Md ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

Achieving precise and predictable motion remains a persistent challenge for microelectromechanical systems (MEMS), where many actuators respond ...

For a project in Bangladesh, Prof. Mushfiq Mobarak and his team used machine-learning models applied to mobile phone records ...

Peer review has met its match.

Researchers demonstrate fourfold improvement to LED steering results after enlisting the help of some good old-fashion AI Boffins at the Department of Energy's Sandia National Labs are working to ...