Sequential Bayesian Experimental Design for Process Optimization with Stochastic Binary Outcomes
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Publisher
Elsevier
Reference6 articles.
1. Probability-Based Design of Experiments for Batch Process Optimization with End-Point Specifications;Colombo;Ind. Eng. Chem. Res.,2016
2. Gaussian Processes for Machine Learning;Rasmussen,2006
3. Taking the Human Out of the loop: A Review of Bayesian Optimization;Shahriari;Proceedings of the IEEE,2016
4. Expensive Function Optimization with Stochastic Binary Outcomes;Tesch,2013
5. Nonlinear Model Predictive Control of End-Use Properties in Batch Reactors;Valappil;AIChE J.,2002
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