Results 191 to 200 of about 289,279 (277)

Tone Mapping of HDR Images via Meta-Guided Bayesian Optimization and Virtual Diffraction Modeling. [PDF]

Sensors (Basel)
Huang D, Zheng X, Li J, Zhan R, Dong J, Wen Y, Mao X, Chen Y, Chen Y.   +8 more
europepmc   +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

Bayesian optimization of capillary pressure data in hydraulic flow units using NMR. [PDF]

Sci Rep
Jehanzaib H, Zahoor MK, Haris M, Saleem Y, Ismail A.   +4 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

Automated Spectral Preprocessing via Bayesian Optimization for Chemometric Analysis of Milk Constituents. [PDF]

Foods
Babatunde HA, McDougal OM, Andersen T.
europepmc   +1 more source

Optimal Bayesian mechanisms [PDF]

, 2011
openaire   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Quantitative Elemental Oxides Analysis of Rock Cuttings Using Laser-Induced Breakdown Spectroscopy Coupled with Bayesian Optimization and Support Vector Machine. [PDF]

ACS Omega
Abu Alsaud S, Swanson A.
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source