Predicting molecular dipole moments by combining atomic partial charges
and atomic dipoles

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Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

27 March 2020

Michele Ceriotti

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Papers citing "Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles"

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Title
SchNetPack 2.0: A neural network toolbox for atomistic machine learning Kristof T. Schütt Stefaan S. P. Hessmann Niklas W. A. Gebauer Jonas Lederer M. Gastegger 83 65 0 11 Dec 2022
Synthetic data enable experiments in atomistic machine learning John L A Gardner Z. Beaulieu Volker L. Deringer 70 9 0 29 Nov 2022
Electronic-structure properties from atom-centered predictions of the electron density Andrea Grisafi Alan M Lewis M. Rossi Michele Ceriotti 100 20 0 28 Jun 2022
Efficient and Accurate Physics-aware Multiplex Graph Neural Networks for 3D Small Molecules and Macromolecule Complexes Shuo-feng Zhang Yang Liu Lei Xie GNN AI4CE 84 12 0 06 Jun 2022
Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning Jiace Sun Lixue Cheng Thomas F. Miller 74 3 0 31 May 2022
Predicting hot-electron free energies from ground-state data Chiheb Ben Mahmoud Federico Grasselli Michele Ceriotti AI4CE 19 7 0 11 May 2022
Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space Lixue Cheng Jiace Sun Thomas F. Miller 48 13 0 21 Apr 2022
Informing Geometric Deep Learning with Electronic Interactions to Accelerate Quantum Chemistry Zhuoran Qiao Anders S. Christensen Matthew Welborn F. Manby Anima Anandkumar Thomas F. Miller 134 74 0 31 May 2021
Equivariant message passing for the prediction of tensorial properties and molecular spectra Kristof T. Schütt Oliver T. Unke M. Gastegger 118 545 0 05 Feb 2021
Multi-scale approach for the prediction of atomic scale properties Andrea Grisafi Jigyasa Nigam Michele Ceriotti 41 31 0 27 Aug 2020
Deep Learning for UV Absorption Spectra with SchNarc: First Steps Towards Transferability in Chemical Compound Space Julia Westermayr P. Marquetand 88 53 0 15 Jul 2020
Machine learning for electronically excited states of molecules Julia Westermayr P. Marquetand 71 266 0 10 Jul 2020
Learning the electronic density of states in condensed matter Chiheb Ben Mahmoud A. Anelli Gábor Csányi Michele Ceriotti 42 55 0 21 Jun 2020
Feature Optimization for Atomistic Machine Learning Yields A Data-Driven Construction of the Periodic Table of the Elements M. J. Willatt Félix Musil Michele Ceriotti 40 50 0 30 Jun 2018
Machine Learning Molecular Dynamics for the Simulation of Infrared Spectra M. Gastegger J. Behler P. Marquetand AI4CE 67 340 0 16 May 2017
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning M. Rupp A. Tkatchenko K. Müller O. A. von Lilienfeld AI4CE 242 1,593 0 12 Sep 2011