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.
Multi-objective Bayesian algorithm automatically discovers low-cost high-growth serum- free media for cellular agriculture application
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.