Maximizing mRNA vaccine production with Bayesian optimization
Sign Up to like & getrecommendations! Published in 2022 at "Biotechnology and Bioengineering"
DOI: 10.1002/bit.28216
Abstract: Messenger RNA (mRNA) vaccines are a new alternative to conventional vaccines with a prominent role in infectious disease control. These vaccines are produced in in vitro transcription (IVT) reactions, catalyzed by RNA polymerase in cascade… read more here.
Keywords: bayesian optimization; ivt reaction; production; vaccine ... See more keywords
Optimal design of dielectric flat lens utilizing Bayesian optimization
Sign Up to like & getrecommendations! Published in 2021 at "Microwave and Optical Technology Letters"
DOI: 10.1002/mop.32837
Abstract: In recent years, various kinds of optimal design approaches are intensively studied for exploring novel and higher performance microwave and optical devices beyond human knowledge. In this article, we first apply a design approach based… read more here.
Keywords: design; optimal design; dielectric flat; optimization ... See more keywords
Using CNN with Bayesian optimization to identify cerebral micro-bleeds
Sign Up to like & getrecommendations! Published in 2020 at "Machine Vision and Applications"
DOI: 10.1007/s00138-020-01087-0
Abstract: This article studies the problem of detecting cerebral micro-bleeds (CMBs) using a convolutional neural network (CNN). Cerebral micro-bleeds (CMBs) are increasingly recognized neuroimaging findings, occurring with cerebrovascular diseases, dementia, and normal aging. Naturally enough, it… read more here.
Keywords: cerebral micro; micro bleeds; using cnn; bayesian optimization ... See more keywords
A multi-fidelity Bayesian optimization approach based on the expected further improvement
Sign Up to like & getrecommendations! Published in 2020 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-020-02772-4
Abstract: Sampling efficiency is important for simulation-based design optimization. While Bayesian optimization (BO) has been successfully applied in engineering problems, the cost associated with large-scale simulations has not been fully addressed. Extending the standard BO approaches… read more here.
Keywords: fidelity; bayesian optimization; fidelity bayesian; multi fidelity ... See more keywords
Route planning for multiple surveillance autonomous drones using a discrete firefly algorithm and a Bayesian optimization method
Sign Up to like & getrecommendations! Published in 2018 at "Artificial Life and Robotics"
DOI: 10.1007/s10015-018-0454-x
Abstract: This paper focuses on the planning of routes for autonomous drones used for the surveillance of a given area. Routes consist of permutations of checkpoints selected by a human supervisor. The permutations are evaluated by… read more here.
Keywords: autonomous drones; surveillance; bayesian optimization; firefly algorithm ... See more keywords
Filtering Bayesian optimization approach in weakly specified search space
Sign Up to like & getrecommendations! Published in 2018 at "Knowledge and Information Systems"
DOI: 10.1007/s10115-018-1238-2
Abstract: Bayesian optimization (BO) has recently emerged as a powerful and flexible tool for hyper-parameter tuning and more generally for the efficient global optimization of expensive black-box functions. Systems implementing BO have successfully solved difficult problems… read more here.
Keywords: search space; space; weakly specified; bayesian optimization ... See more keywords
Combining Bayesian optimization and Lipschitz optimization
Sign Up to like & getrecommendations! Published in 2019 at "Machine Learning"
DOI: 10.1007/s10994-019-05833-y
Abstract: Bayesian optimization and Lipschitz optimization have developed alternative techniques for optimizing black-box functions. They each exploit a different form of prior about the function. In this work, we explore strategies to combine these techniques for… read more here.
Keywords: lipschitz optimization; bayesian optimization; combining bayesian; optimization ... See more keywords
High-dimensional Bayesian optimization with projections using quantile Gaussian processes
Sign Up to like & getrecommendations! Published in 2020 at "Optimization Letters"
DOI: 10.1007/s11590-019-01433-w
Abstract: Key challenges of Bayesian optimization in high dimensions are both learning the response surface and optimizing an acquisition function. The acquisition function selects a new point to evaluate the black-box function. Both challenges can be… read more here.
Keywords: dimensional bayesian; optimization; optimization projections; high dimensional ... See more keywords
Prediction of tubular solar still performance by machine learning integrated with Bayesian optimization algorithm
Sign Up to like & getrecommendations! Published in 2021 at "Applied Thermal Engineering"
DOI: 10.1016/j.applthermaleng.2020.116233
Abstract: Presented is a new generation prediction model of a tubular solar still (TSS) productivity utilizing two machine learning (ML) techniques, namely:Random forest (RF) and Artificial neural network (ANN). Prediction models were conducted based on experimental… read more here.
Keywords: machine learning; solar still; bayesian optimization; tubular solar ... See more keywords
Efficiently searching through large tACS parameter spaces using closed-loop Bayesian optimization
Sign Up to like & getrecommendations! Published in 2019 at "Brain Stimulation"
DOI: 10.1016/j.brs.2019.07.003
Abstract: Background Selecting optimal stimulation parameters from numerous possibilities is a major obstacle for assessing the efficacy of non-invasive brain stimulation. Objective We demonstrate that Bayesian optimization can rapidly search through large parameter spaces and identify… read more here.
Keywords: bayesian optimization; stimulation; efficiently searching; optimization ... See more keywords
Machine-learning-assisted fabrication: Bayesian optimization of laser-induced graphene patterning using in-situ Raman analysis
Sign Up to like & getrecommendations! Published in 2020 at "Carbon"
DOI: 10.1016/j.carbon.2020.05.087
Abstract: Abstract The control of the physical, chemical, and electronic properties of laser-induced graphene (LIG) is crucial in the fabrication of flexible electronic devices. However, the optimization of LIG production is time-consuming and costly. Here, we… read more here.
Keywords: machine learning; bayesian optimization; fabrication; optimization ... See more keywords