A focus on molecular representation learning for the prediction of chemical properties
Yonatan Harnik, Anat Milo
Abstract
Molecular representation learning (MRL) holds significant potential for predicting diverse chemical properties. In this focus article, we will provide context for applications of MRL in chemistry and the significance of King-Smith's recently published work within this evolving field.
Topics & Concepts
Representation (politics)Focus (optics)Context (archaeology)Field (mathematics)Computer scienceCognitive scienceChemistryArtificial intelligenceData sciencePsychologyMathematicsBiologyPhysicsPolitical sciencePure mathematicsPaleontologyLawOpticsPoliticsComputational Drug Discovery MethodsMachine Learning in Materials ScienceCrystallography and molecular interactions