Bayesian optimizationParameter identificationIn this work, we advocate using Bayesian techniques for inversely identifying material parameters for multiscale crystal plasticity models. Multiscale approaches for
We explore the inverse rendering problem of procedural material parameter estimation from photographs, presenting a unified view of the problem in a Bayesian framework. In addition to computing point estimates of the parameters by optimization, our framework uses a Markov Chain Monte Carlo approach to...
This study introduced the random forest (RF) and extreme gradient boosting (XGBoost) approaches that combine the state-of-the-art Bayesian hyper-parameter optimization (BHPO) and 5-fold cross-validation for density prediction. The pavement density data collected from the literature, laboratory, and...
The core of Bayesian Optimization (BO) is to build a surrogate model of the target function using a Gaussian Process (GP) regression and iteratively select points to evaluate based on this model. The GP can model a rich distribution over functions and depends entirely on the choice of the co...
Instead of tuning the network parameter by trial and error, the Bayesian parameter optimization algorithm was implemented to find the optimal set of parameters of the deep convolutional network that yields the minimum mean square error. The proposed algorithm was compared with a previously developed ...
Bayesian optimization (BO) is an indispensable tool to optimize objective functions that either do not have known functional forms or are expensive to evaluate. Currently, optimal experimental design is always conducted within the workflow of BO leading
Rapid discovery and synthesis of future materials requires intelligent data acquisition strategies to navigate large design spaces. A popular strategy is Bayesian optimization, which aims to find candidates that maximize material properties; however, materials design often requires finding specific subsets of...
4. The method assessing reliability of the casings in marine gas reservoirs based on the Bayesian optimization 4.1. The assessment method based on the standard of collapsing strength The assessment method based on the standard of collapsing strength (Zhu and Liu, 2018) (including ISO standard (ISO...
Bayesian optimization algorithm has been applied successfully in different areas in chemistry, for instance material design [25,26,27] and high-throughput virtual screening [28]. The general idea of BOA is to construct an approximate surrogate model of the objective function, f(x), and then ...
Its primary function is to guide the optimization algorithm in selecting the next point x in the hyperparameter space to evaluate. The acquisition function quantifies the expected utility or improvement of evaluating the objective function at a particular point x, based on the existing data and ...