Quantitative experiments are essential for investigating, uncovering, and confirming our understanding of complex systems, necessitating the use of effective and robust experimental designs. Despite ...
Among machine learning techniques, Bayesian optimization (BO) has emerged as the go-to choice for optimizing the design of experiments in the chemical domain 1,2,3,4. BO, grounded in a probabilistic ...
Bayesian experimental design is a tool for guiding experiments founded on the principle of expected information gain. I.e., which experiment design will inform the most about the model can be ...
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