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.
High-throughput screening of catalytically active inclusion bodies using laboratory automation and Bayesian optimization
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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.