A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules

10 January 2019

Papers citing "A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules"

6 / 6 papers shown

Title
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 24 2 0 31 May 2022
DeePKS: a comprehensive data-driven approach towards chemically accurate density functional theory Yixiao Chen Linfeng Zhang Han Wang E. Weinan 11 72 0 01 Aug 2020
OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features Zhuoran Qiao Matthew Welborn Anima Anandkumar F. Manby Thomas F. Miller AI4CE 24 214 0 15 Jul 2020
Machine learning for electronically excited states of molecules Julia Westermayr P. Marquetand 17 257 0 10 Jul 2020
A deep neural network for molecular wave functions in quasi-atomic minimal basis representation M. Gastegger A. McSloy M. Luya Kristof T. Schütt R. Maurer 11 46 0 11 May 2020
Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions Kristof T. Schütt M. Gastegger A. Tkatchenko K. Müller R. Maurer AI4CE 29 381 0 24 Jun 2019