Active learning of chemical reaction networks<i>via</i>probabilistic graphical models and Boolean reaction circuits
Maximilian Cohen, Tejas Goculdas, Dionisios G. Vlachos
Abstract
Reaction networks are identified with active learning design of experiments using Bayesian statistics and Boolean principles in a generalizable methodology.
Topics & Concepts
Bayesian networkComputer scienceProbabilistic logicGraphical modelBoolean functionElectronic circuitTheoretical computer scienceMachine learningArtificial intelligenceAlgorithmEngineeringElectrical engineeringAnalytical Chemistry and ChromatographyAdvanced Control Systems OptimizationGene Regulatory Network Analysis