相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Fermionic neural-network states for ab-initio electronic structure
Kenny Choo et al.
NATURE COMMUNICATIONS (2020)
Ab initio solution of the many-electron Schrodinger equation with deep neural networks
David Pfau et al.
PHYSICAL REVIEW RESEARCH (2020)
PhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments, and Partial Charges
Oliver T. Unke et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2019)
Backflow Transformations via Neural Networks for Quantum Many-Body Wave Functions
Di Luo et al.
PHYSICAL REVIEW LETTERS (2019)
Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions
K. T. Schuett et al.
NATURE COMMUNICATIONS (2019)
Solving many-electron Schrodinger equation using deep neural networks
Jiequn Han et al.
JOURNAL OF COMPUTATIONAL PHYSICS (2019)
Transferable Machine-Learning Model of the Electron Density
Andrea Grisafi et al.
ACS CENTRAL SCIENCE (2019)
SchNet - A deep learning architecture for molecules and materials
K. T. Schuett et al.
JOURNAL OF CHEMICAL PHYSICS (2018)
Alchemical and structural distribution based representation for universal quantum machine learning
Felix A. Faber et al.
JOURNAL OF CHEMICAL PHYSICS (2018)
Method to Solve Quantum Few-Body Problems with Artificial Neural Networks
Hiroki Saito
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN (2018)
Nonlinear Network Description for Many-Body Quantum Systems in Continuous Space
Michele Ruggeri et al.
PHYSICAL REVIEW LETTERS (2018)
Fast and accurate quantum Monte Carlo for molecular crystals
Andrea Zen et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2018)
Transferability in Machine Learning for Electronic Structure via the Molecular Orbital Basis
Matthew Welborn et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2018)
H4: A model system for assessing the performance of diffusion Monte Carlo calculations using a single Slater determinant trial function
Kevin Gasperich et al.
JOURNAL OF CHEMICAL PHYSICS (2017)
Solving the quantum many-body problem with artificial neural networks
Giuseppe Carleo et al.
SCIENCE (2017)
ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost
J. S. Smith et al.
CHEMICAL SCIENCE (2017)
Machine learning unifies the modeling of materials and molecules
Albert P. Bartok et al.
SCIENCE ADVANCES (2017)
Machine learning of accurate energy-conserving molecular force fields
Stefan Chmiela et al.
SCIENCE ADVANCES (2017)
Hard Numbers for Large Molecules: Toward Exact Energetics for Supramolecular Systems
Alberto Ambrosetti et al.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2014)
Quantum Monte Carlo and Related Approaches
Brian M. Austin et al.
CHEMICAL REVIEWS (2012)
Multireference Nature of Chemistry: The Coupled-Cluster View
Dmitry I. Lyakh et al.
CHEMICAL REVIEWS (2012)
Multideterminant Wave Functions in Quantum Monte Carlo
Miguel A. Morales et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2012)
Optimizing large parameter sets in variational quantum Monte Carlo
Eric Neuscamman et al.
PHYSICAL REVIEW B (2012)
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
Matthias Rupp et al.
PHYSICAL REVIEW LETTERS (2012)
Quantum Monte Carlo study of the first-row atoms and ions
P. Seth et al.
JOURNAL OF CHEMICAL PHYSICS (2011)
Continuum variational and diffusion quantum Monte Carlo calculations
R. J. Needs et al.
JOURNAL OF PHYSICS-CONDENSED MATTER (2010)
Stochastic Coupled Cluster Theory
Alex J. W. Thom
PHYSICAL REVIEW LETTERS (2010)
Fermion Monte Carlo without fixed nodes: A game of life, death, and annihilation in Slater determinant space
George H. Booth et al.
JOURNAL OF CHEMICAL PHYSICS (2009)
Full optimization of Jastrow-Slater wave functions with application to the first-row atoms and homonuclear diatomic molecules
Julien Toulouse et al.
JOURNAL OF CHEMICAL PHYSICS (2008)
Energies of the first row atoms from quantum Monte Carlo
M. D. Brown et al.
JOURNAL OF CHEMICAL PHYSICS (2007)
Generalized neural-network representation of high-dimensional potential-energy surfaces
Joerg Behler et al.
PHYSICAL REVIEW LETTERS (2007)
Inhomogeneous backflow transformations in quantum Monte Carlo calculations
P. Lopez Rios et al.
PHYSICAL REVIEW E (2006)
Scheme for adding electron-nucleus cusps to Gaussian orbitals
A Ma et al.
JOURNAL OF CHEMICAL PHYSICS (2005)
Computational complexity and fundamental limitations to fermionic quantum monte carlo simulations
M Troyer et al.
PHYSICAL REVIEW LETTERS (2005)
Computing accurate forces in quantum Monte Carlo using Pulay's corrections and energy minimization
M Casalegno et al.
JOURNAL OF CHEMICAL PHYSICS (2003)
Quantum Monte Carlo simulations of solids
WMC Foulkes et al.
REVIEWS OF MODERN PHYSICS (2001)