Extending machine learning beyond interatomic potentials for predicting molecular properties
Nikita Fedik, R.I. Zubatyuk, Maksim Kulichenko, Nicholas Lubbers, Justin S. Smith, Benjamin Nebgen, Richard A. Messerly, Ying Wai Li, Alexander I. Boldyrev, Kipton Barros, Olexandr Isayev, Sergei Tretiak
Topics & Concepts
GeneralityDipoleMachine learningComputer scienceInteratomic potentialArtificial intelligenceQuantum chemicalArtificial neural networkTransferabilityStatistical physicsForce field (fiction)Molecular dynamicsPhysicsChemistryComputational chemistryQuantum mechanicsMoleculePsychotherapistLogitPsychologyMachine Learning in Materials ScienceComputational Drug Discovery MethodsProtein Structure and Dynamics