Results 171 to 180 of about 2,475,679 (305)

Efficient Super-Resolution Bayesian Eletromagnetic Brain Imaging. [PDF]

IEEE Trans Biomed Eng
Cai C, Qi X, Yan J, Shang Y, Sekihara K, Wu W, Nagarajan SS.   +6 more
europepmc   +1 more source

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source

Adaptive modelling approach for predicting causes of death: insights from verbal autopsy data in Tanzania. [PDF]

Int Health
Tunga M, Chambua J, Lungo J.
europepmc   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Combining K-fold cross validation with bayesian hyperparameter optimization for accuracy enhancement of land cover and land use classification. [PDF]

Sci Rep
Heidari P, Milan A.
europepmc   +1 more source

Bayesian structure learning in graphical models

, 2016
This thesis consists of two papers studying structure learning in probabilistic graphical models for both undirected graphs anddirected acyclic graphs (DAGs). Paper A, presents a novel family of graph theoretical algorithms, called the junction tree expanders, that incrementally construct junction trees for decomposable graphs.
openaire   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

Integrating Blockchain Traceability and Deep Learning for Risk Prediction in Grain and Oil Food Safety. [PDF]

Foods
Ge H, Fan K, Zhang Y, Jiang Y, Wang S, Chen Z.   +5 more
europepmc   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

Coronary artery disease prediction using Bayesian-optimized support vector machine with feature selection. [PDF]

Front Netw Physiol
Baratpur AZ, Vahdat-Nejad H, Arslan E, Hassannataj Joloudari J, Gaftandzhieva S.   +4 more
europepmc   +1 more source