An extension of PFGS adds posterior probability of constraint satisfaction and Monte Carlo robustness estimation as Pareto objectives for interactive candidate selection in Bayesian optimization, demonstrated on an 8D CHO cell culture simulator.
Efficient Tuning of an Isotope Separation Online System Through Safe Bayesian Optimization with Simulation-Informed Gaussian Process for the Constraints
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A Human-in-the-Loop Bayesian Optimization Framework for Constraint-Aware Bioprocess Development
An extension of PFGS adds posterior probability of constraint satisfaction and Monte Carlo robustness estimation as Pareto objectives for interactive candidate selection in Bayesian optimization, demonstrated on an 8D CHO cell culture simulator.