Automated design of nonreciprocal thermal emitters via Bayesian optimization

B Do, SJ Ghalekohneh, T Adebiyi, B Zhao… - Journal of Quantitative …, 2025 - Elsevier
Nonreciprocal thermal emitters that break Kirchhoff's law of thermal radiation promise
exciting applications for thermal and energy applications. The design of the bandwidth and …

Multi-fidelity machine learning for uncertainty quantification and optimization

R Zhang, N Alemazkoor - Journal of Machine Learning for …, 2024 - dl.begellhouse.com
In system analysis and design optimization, multiple computational models are typically
available to represent a given physical system. These models can be broadly classified as …

Partitioned Surrogates and Thompson Sampling for Multidisciplinary Bayesian Optimization

S Baars, J Parekh, I Antonau, P Bekemeyer… - arXiv preprint arXiv …, 2024 - arxiv.org
The long runtime associated with simulating multidisciplinary systems challenges the use of
Bayesian optimization for multidisciplinary design optimization (MDO). This is particularly the …