Results 171 to 180 of about 523,565 (314)

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

Vitamin D Receptor Gene Polymorphisms Differentiated Between Tuberculosis Disease and Infection: Causal Association Study

Infection and Drug Resistance
Jaina Razbek,1 Yanggui Chen,2 Jiandong Yang,2 Yaying Zhang,1 Baofeng Wen,1 Junan Wang,1 Xiaomin Wang,1 Guliziba Kuerbanjiang,1 Abulikemu Aili,1 Mingqin Cao1 1Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical ...
Razbek J, Chen Y, Yang J, Zhang Y, Wen B, Wang J, Wang X, Kuerbanjiang G, Aili A, Cao M   +9 more
doaj  

Simplifying fractional polynomials in Bayesian network meta-analysis via variable powers. [PDF]

J Comp Eff Res
Verhoek A, Ouwens MJ, Heeg B, Jansman FG, Postma MJ.   +4 more
europepmc   +1 more source

Dynamic bayesian networks modelling maintenance strategies: Prevention of broken rails

, 2008
Laurent Bouillaut, Olivier François, Philippe Leray, Patrice Aknin, Stéphane Dubois   +4 more
openalex   +1 more source

Code: Stochastic Weight Sharing for Bayesian Neural Networks

Moule Lin, Goetz Botterweck
openalex   +1 more source

FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

Advanced Intelligent Discovery, EarlyView.
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker, Enzo Raffaele Moretti, Jin Hyun Chang, Tejs Vegge   +3 more
wiley   +1 more source

Efficacy of MAO-B and COMT inhibitors on quality of life in patients with Parkinson's disease: a Bayesian network meta-analysis. [PDF]

Front Neurol
Shim SR, Jung YJ, Kwon KY, Rhee TG, Lee SM.   +4 more
europepmc   +1 more source

Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care [PDF]

, 2019
Anna-Lena Popkes, Hiske Overweg, Ari Ercole, Yingzhen Li, José Miguel Hernández-Lobato, Yordan Zaykov, Cheng Zhang   +6 more
openalex   +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

Comparative effectiveness of orthopedic teaching methods in China: a Bayesian network meta-analysis of randomized trials. [PDF]

BMC Med Educ
Gu P, Xu Z, Zhang Z, Wen Y, Jia Y, Du Y, Wen T, Man C, Jia Z, Wu Y, Li W.   +10 more
europepmc   +1 more source