Machine learning identifies catalyst 'sweet spot' for greener urea from waste gases

Urea is an extremely important chemical, especially for fertilizers. But, making urea is energy intensive and relies heavily ...
Decrypt

Tencent's New Hy3 AI Model Is the Most Efficient Chinese LLM No One's Talking About

Tencent just open-sourced Hy3 preview, a model that punches above its weight on coding agents, reasoning, and search—built in ...
EurekAlert!

How an algorithm is curing 3D printing’s cracking problem

In International Journal of Extreme Manufacturing, researchers at the University of Science and Technology Beijing developed ...
IEEE

Gaussian Mixture Model Based Bayesian Learning for Sparse Channel Estimation in Orthogonal Time Frequency Space Modulated Systems

Abstract: A novel Gaussian mixture model (GMM)–aided sparse Bayesian learning (SBL) framework is proposed for channel state information (CSI) estimation in orthogonal time-frequency space (OTFS) ...
GitHub

MLIP (Machine Learning Interatomic Potential) plugins for Gaussian 16 External interface.

All backends provide energy, gradient, and analytical Hessian for Gaussian 16. An optional implicit-solvent correction (xTB) is also available via --solvent. The model server starts automatically and ...
IEEE

Learning-Based Model Predictive Control With High-Probability Safety Using Gaussian Mixture Models

Abstract: This article introduces a learning-based model predictive control (MPC) framework that leverages Gaussian mixture models (GMMs) to address dynamic system uncertainties effectively. To ...
The American Journal of Managed Care

Novel Machine Learning Model Improves MASLD Detection in Type 2 Diabetes

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...
Scientific Research Publishing

Rasmussen, C.E. and Williams, C.K.I. (2005) Gaussian Processes for Machine Learning. The MIT Press.

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...
C&EN

Integrating Machine Learning into Free Energy Perturbation Workflows

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Free energy perturbation (FEP) methods are among the most accurate tools in ...
Live Science

Scientists use quantum machine learning to create semiconductors for the first time – and it could transform how chips are made

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...