techxplore15h
Mismatched training environments could help AI agents perform better in uncertain conditions
A home robot trained to perform household tasks in a factory may fail to effectively scrub the sink or take out the trash ...
Digi Times5dOpinion
Simeon Denis Poisson's work in probability theory underpins modern AI and machine learning applications
The Poisson distribution is widely used in artificial intelligence (AI) and machine learning. In Bayesian inference, ...
News Medical7d
Social interventions could lead to major drop in national HIV incidence
Researchers at the University of Massachusetts Amherst have quantified the impacts of a constellation of social factors on ...
PC Magazine17d
The Best Online Learning Services for Kids in 2025
Send your kids to these sites to help them learn, study, indulge their curiosity, and get a fresh perspective on academic subjects. I've been contributing to PCMag since 2011 in a variety of ways ...
C&EN23d
MAGPIE: A Machine Learning Approach to Decipher Protein–Protein Interactions in Human Plasma
Department of Biochemistry, Microbiology and Immunology and Ottawa Institute of Systems Biology, Faculty of Medicine, University of Ottawa, 451 Smyth Road, Ottawa, Ontario K1H 8M5, Canada Department ...
C&EN27d
Efficient Sampling for Machine Learning Electron Density and Its Response in Real Space
Hefei National Research Center for Physical Sciences at the Microscale, Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026, China Key Laboratory of ...
Frontiers28d
Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia
Purpose: The purpose of this study is to investigate whether machine learning with dosiomic, radiomic, and demographic features allows for xerostomia risk assessment more precise than normal tissue ...