Adaptive Simulation Selection for the Discovery of the Ground State Line of Binary Alloys with a Limited Computational Budget-Reference-Cited by-同舟云学术

Adaptive Simulation Selection for the Discovery of the Ground State Line of Binary Alloys with a Limited Computational Budget

Published:2017 Issue: Volume: Page:185-211
ISSN:1069-5265
Container-title:Recent Progress and Modern Challenges in Applied Mathematics, Modeling and Computational Science
language:
Short-container-title:

Author:

Kristensen Jesper,Bilionis Ilias,Zabaras Nicholas

Publisher

Springer New York

Link

http://link.springer.com/content/pdf/10.1007/978-1-4939-6969-2_6

Reference77 articles.

1. Bahn SR, Jacobsen KW (2002) An object-oriented scripting interface to a legacy electronic structure code. Computing in Science and Engineering 4(3):56–66

2. Bayes M, Price M (1763) An essay towards solving a problem in the doctrine of chances. by the late rev. Mr. Bayes, frs communicated by Mr. Price, in a letter to John Canton, amfrs. Philosophical Transactions (1683–1775) pp 370–418

3. Bertsekas D (2007) Dynamic Programming and Optimal Control, 4th edn. Athena Scientific

4. Bilionis I, Zabaras N (2012) Multi-output local Gaussian process regression: Applications to uncertainty quantification. Journal of Computational Physics 231(17):5718–5746, DOI Doi10.1016/J.Jcp.2012.04.047, URL ://WOS:000305915400009http://ac.els-cdn.com/S0021999112002513/1-s2.0-S0021999112002513-main.pdf?_tid=38a01da2-53ab-11e4-b833-00000aab0f6c&acdnat=1413295738_53a4d40cd278f24f49ec27babcdcd03c

5. Bilionis I, Zabaras N (2012) Multidimensional adaptive relevance vector machines for uncertainty quantification. SIAM Journal on Scientific Computing 34(6):B881–B908, DOI Doi 10.1137/120861345, URL ://WOS:000312737900020http://epubs.siam.org/doi/pdf/10.1137/120861345

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Bayesian optimization acquisition functions for accelerated search of cluster expansion convex hull of multi-component alloys;npj Computational Materials;2024-09-08

2. Probabilistic Transfer Learning through Ensemble Probabilistic Deep Neural Network;AIAA SCITECH 2023 Forum;2023-01-19

3. Transfer Learning Based Modeling of Industrial Turbine Airfoil Characteristics;AIAA SCITECH 2022 Forum;2022-01-03

4. An exploitation-enhanced multi-objective efficient global optimization algorithm for expensive aerodynamic shape optimizations;Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering;2021-07-17

5. Scalable Fully Bayesian Gaussian Process Modeling and Calibration With Adaptive Sequential Monte Carlo for Industrial Applications;Journal of Mechanical Design;2021-03-24