Results 161 to 170 of about 691,007 (262)

Bayesian network structure learning by opposition-based learning. [PDF]

Sci Rep
Sun B, Zhang X, Jiang J, Gong J, Lin D.
europepmc   +1 more source

Knowledge-based and data-driven underground pressure forecasting based on graph structure learning. [PDF]

Int J Mach Learn Cybern, 2022
Wang Y, Liu M, Huang Y, Zhou H, Wang X, Wang S, Du H.   +6 more
europepmc   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Efficient structure learning of gene regulatory networks with Bayesian active learning. [PDF]

BMC Bioinformatics
Sándor D, Antal P.
europepmc   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

TAN-FGBMLE: Tree-Augmented Naive Bayes Structure Learning Based on Fast Generative Bootstrap Maximum Likelihood Estimation for Continuous-Variable Classification. [PDF]

Entropy (Basel)
Wei C, Zhang T, Li C, Wang P, Ye Z.
europepmc   +1 more source

Potential cognitive and neural benefits of a computerised cognitive training programme based on Structure Learning in healthy adults: study protocol for a randomised controlled trial. [PDF]

Trials, 2023
Liu CL, Cheng X, Choo BL, Hong M, Teo JL, Koo WL, Tan JYJ, Ubrani MB, Suckling J, Gulyás B, Leong V, Kourtzi Z, Sahakian B, Robbins T, Chen AS.   +14 more
europepmc   +1 more source

The PRIMA Thesaurus for Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa, Alexey Boubnov, Dario De Angelis, Catriona Eschke, Maximilian Kabbe, Felix Kraus, Mirco Panighel, Richard Thelen, Davide Valentinis   +8 more
wiley   +1 more source

Correction: A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools

Frontiers in Systems Biology
Francesco Canonaco, Francesco Canonaco, Joverlyn Gaudillo, Nicole Astrologo, Fabio Stella, Enzo Acerbi   +5 more
doaj   +1 more source

Assessing Credibility in Bayesian Networks Structure Learning. [PDF]

Entropy (Basel)
Barth V, Serrão F, Maciel C.
europepmc   +1 more source