A transfer learning protocol for chemical catalysis using a recurrent neural network adapted from natural language processing
Sukriti Singh, Raghavan B. Sunoj
Abstract
A transfer learning protocol for yield and enantioselectivity predictions of transition metal- and organo-catalytic reactions, suitable for small (<400) to large (>4000) data regimes.
Topics & Concepts
Protocol (science)Transfer of learningCatalysisYield (engineering)Computer scienceArtificial neural networkKnowledge transferTransfer (computing)Artificial intelligenceChemistryNatural language processingOrganic chemistryKnowledge managementMedicinePhysicsParallel computingThermodynamicsPathologyAlternative medicineMachine Learning in Materials ScienceAsymmetric Hydrogenation and CatalysisComputational Drug Discovery Methods