Results 151 to 160 of about 4,909,083 (351)

Multivariate Bayesian Optimization of CoO Nanoparticles for CO₂ Hydrogenation Catalysis [PDF]

Lanja R. Karadaghi, Emily M. Williamson, Anh T. To, Allison P. Forsberg, Kyle D. Crans, Craig L. Perkins, Steven C. Hayden, Nicole J. LiBretto, Frederick G. Baddour, Daniel A. Ruddy, Noah Malmstadt, Susan E. Habas, Richard L. Brutchey   +12 more
openalex   +1 more source

Explainable Bayesian Optimization

Abstract Manual parameter tuning of cyber-physical systems is a common practice, but it is labor-intensive. Bayesian Optimization (BO) offers an automated alternative, yet its black-box nature reduces trust and limits human-BO collaborative system tuning. Experts struggle to interpret BO recommendations due to the lack of explanations.
Tanmay Chakraborty, Christian Wirth, Christin Seifert   +2 more
openaire   +2 more sources

Nanozymes Integrated Biochips Toward Smart Detection System

Advanced Science, EarlyView.
This review systematically outlines the integration of nanozymes, biochips, and artificial intelligence (AI) for intelligent biosensing. It details how their convergence enhances signal amplification, enables portable detection, and improves data interpretation.
Dongyu Chen, Wang Zheng, Zhihui Zhang, Shenping Yu, Xinxin Hang, Han Wu, Xiao‐Wei Xiang, Wei Mu, Yanli Jiao, Zaizai Dong, Lingqian Chang   +10 more
wiley   +1 more source

Stacking sequence optimization of composite laminates for maximum fundamental frequency using Bayesian optimization computational framework

Results in Engineering
A computational framework combined with the commercial finite element software Abaqus and Bayesian optimization algorithm is proposed. The proposed computational framework leverages the Gaussian process based-probabilistic capability in Bayesian ...
Shih-Ting Yang, Yu-Jui Liang
doaj   +1 more source

Bayesian Optimization-based Modular Indirect Adaptive Control for a Class of Nonlinear Systems

, 2016
Mouhacine Benosman, Amir‐massoud Farahmand   +1 more
openalex   +1 more source

AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning [PDF]

, 2018
Ahmed M. Alaa, Mihaela van der Schaar
openalex   +1 more source

Reconstructing Coherent Functional Landscape From Multi‐Modal Multi‐Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process

Advanced Science, EarlyView.
This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang, Bowen Fu, Chuanchao Zhang, Xiaoping Liu   +3 more
wiley   +1 more source

Traditional or adaptive design of experiments? A pilot-scale comparison on wood delignification

Heliyon
Traditional design of experiments and response surface methodology are widely used in engineering and process development. Bayesian optimization is an alternative machine learning approach that adaptively selects successive experimental conditions based ...
Hannu Rummukainen, Hanna Hörhammer, Pirkko Kuusela, Jorma Kilpi, Jari Sirviö, Mikko Mäkelä   +5 more
doaj   +1 more source

Bayesian optimization package: PHYSBO

, 2022
Yuichi Motoyama, Ryo Tamura, Kazuyoshi Yoshimi, Kei Terayama, Tsuyoshi Ueno, Koji Tsuda   +5 more
openalex   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source