[2109.13337] DEBOSH: Deep Bayesian Shape Optimization
...For optimization techniques relying on Gaussian Processes, Bayesian Optimization (BO) addresses this issue by exploiting their ability to assess their own accuracy....
https://arxiv.org/abs/2109.13337
Materials design with target-oriented Bayesian optimization
...Materials design using Bayesian optimization (BO) typically focuses on optimizing materials properties by estimating the maxima/minima of unknown functions....
https://www.nature.com/articles/s41524-025-01704-4
DEBOSH: Deep Bayesian Shape Optimization - Neural Concept
...Bayesian Optimization (BO) is an exploration-exploitation procedure that minimizes given black-box function. Uncertainty lies at the core of BO that allows to perform optimization in more efficient and optimal way comparing to deterministic and greedy approaches....
https://www.neuralconcept.com/post/debosh-deep-bayesian-shape-optimization
A physics informed bayesian optimization approach for ...
...In this study, we propose a physics-informed BO approach that integrates physics-infused kernels to effectively leverage both statistical and physical information in the decision-making process. We......
https://www.nature.com/articles/s41524-023-01173-7
Prediction and optimization of airfoil aerodynamic ...
...In this paper, we proposed an innovative Bayesian optimization (BO) coupled with deep learning for rapid airfoil shape optimization to maximize aerodynamic performance of airfoils....
https://pubs.aip.org/aip/pof/article/34/11/117116/2848801/Prediction-and-optimization-of-airfoil-aerodynamic
(PDF) DEBOSH: Deep Bayesian Shape Optimization - ResearchGate
...Our experiments on diverse aerodynamics and structural analysis tasks prove that adding uncertainty to shape optimization significantly improves the quality of resulting shapes and reduces the......
https://www.researchgate.net/publication/354949559_DEBOSH_Deep_Bayesian_Shape_Optimization
DEBOSH: Deep Bayesian Shape Optimization
...DEBOSH utilizes Bayesian Optimization (BO) and Graph Neural Networks (GNNs) in order to effectively explore the space of possible shapes and acquire the best performing samples according to physical properties. Shape optimization is at the heart of many industrial applications, such as aerodynamics, heat transfer, and structural analysis....
https://www.norange.io/projects/debosh_depricated/
Bayesian optimization A tutorial on - Zi Wang
...Unknown priors Bayesian optimization with an unknown prior Estimate ?prior? from data...
https://ziw.mit.edu/pub/bayesopt_tutorial.pdf
bayesian_optimization.ipynb - Colab
...Bayesian optimization incorporates prior belief about f and updates the prior with samples drawn from f to get a posterior that better approximates f. The model used for approximating the......
https://colab.research.google.com/github/krasserm/bayesian-machine-learning/blob/master/bayesian_optimization.ipynb
Benchmarking Five Global Optimization Approaches for Nano ...
...Here, we benchmark five global optimization methods for three typical nano-optical optimization problems: particle swarm optimization, differential evolution, and Bayesian optimization as well as multistart versions of downhill simplex optimization and the limited-memory Broyden?Fletcher?Goldfarb?Shanno (L-BFGS) algorithm....
https://pubs.acs.org/doi/10.1021/acsphotonics.9b00706