Abstract: Due to the characteristics of multi-dimensional, strong coupling and noise of complex industrial data, this paper establishes an energy efficiency recognition and diagnosis model using the ...

Envelope models constitute a class of methods in multivariate regression that seek to identify and exploit a minimal subspace—termed the envelope—that contains all the variation of interest for ...

MMER is a Python package for multivariate mixed-effects regression featuring a modular fixed-effects component. It supports parametric and non-parametric machine learning regressors (neural networks, ...

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...

ABSTRACT: To address the multicoupling effects of stress response in UAV landing gear during touchdown, this study employs a multivariate nonlinear regression approach for multi-objective optimization ...

1 School of Aeronautics and Astronautics, Sun Yat-sen University, Guangzhou, China. 2 School of Science and Technology, Hunan University of Technology, Zhuzhou, China. To address the multicoupling ...

Abstract: Lightning strikes have posed a severe threat to the operational safety of wind turbines. As an additional lightning-protection measure, metal meshes have been deployed on a number of ...

The Python Software Foundation warned users this week that threat actors are trying to steal their credentials in phishing attacks using a fake Python Package Index (PyPI) website. PyPI is a ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Department of Chemical Engineering, Auburn University, Auburn, Alabama 36849, United States Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia ...

article{londschien2025, title={Domain Generalization and Adaptation in Intensive Care with Anchor Regression}, author={Londschien, Malte, Burger, Manuel, R{\"a}tsch ...