Maximizing Thermoelectric Figures of Merit by Uniaxially Straining Indium Selenide
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October 2019
Perspective: Machine learning potentials for atomistic simulations
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November 2016
The atomic simulation environment—a Python library for working with atoms
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June 2017
On the role of gradients for machine learning of molecular energies and forces
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October 2020
Machine Learning for Quantum Mechanical Properties of Atoms in Molecules
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July 2015
Constructing high-dimensional neural network potentials: A tutorial review
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March 2015
Methods for calculating forces within quantum Monte Carlo simulations
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February 2010
A combined first principles study of the structural, magnetic, and phonon properties of monolayer CrI3
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January 2022
Gaussian approximation potentials: A brief tutorial introduction
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April 2015
SchNet – A deep learning architecture for molecules and materials
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June 2018
SchNetPack: A Deep Learning Toolbox For Atomistic Systems
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November 2018
Spin-orbit interactions in electronic structure quantum Monte Carlo methods
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April 2016
Advanced capabilities for materials modelling with Quantum ESPRESSO
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October 2017
sGDML: Constructing accurate and data efficient molecular force fields using machine learning
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July 2019
Insights into one-body density matrices using deep learning
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January 2020
A light weight regularization for wave function parameter gradients in quantum Monte Carlo
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August 2020
Active Learning the Potential Energy Landscape for Water Clusters from Sparse Training Data
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January 2020
Monte Carlo Methods in Ab Initio Quantum Chemistry
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March 1994
Introduction to the diffusion Monte Carlo method
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May 1996
Correlated sampling in quantum Monte Carlo: A route to forces
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June 2000
A Machine-Learning Surrogate Model for ab initio Electronic Correlations at Extreme Conditions
preprint
January 2021
Finding the needle in the haystack: towards solving the protein-folding problem computationally
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October 2017
Toward quantum Monte Carlo forces on heavier ions: Scaling properties
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May 2021
Forces in Molecules
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August 1939
QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion quantum Monte Carlo
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May 2020
Surrogate Hessian accelerated structural optimization for stochastic electronic structure theories
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February 2022
Nexus: A modular workflow management system for quantum simulation codes
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January 2016
An overview of coupled cluster theory and its applications in physics
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January 1991
Accurate forces in quantum Monte Carlo calculations with nonlocal pseudopotentials
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September 2007
Constructing feed-forward artificial neural networks to fit potential energy surfaces for molecular simulation of high-temperature gas flows
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November 2020
A neural network potential-energy surface for the water dimer based on environment-dependent atomic energies and charges
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February 2012
Inferring the quantum density matrix with machine learning
preprint
January 2019
Algorithmic differentiation and the calculation of forces by quantum Monte Carlo
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December 2010
Machine learning for potential energy surfaces: An extensive database and assessment of methods
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June 2019
Energy Derivatives in Real-Space Diffusion Monte Carlo
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December 2021
Tail-regression estimator for heavy-tailed distributions of known tail indices and its application to continuum quantum Monte Carlo data
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June 2019
Differentiable Programming Tensor Networks
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September 2019
Computing forces with quantum Monte Carlo
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September 2000
Quantum Monte Carlo simulations of solids
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January 2001
SIMPLE-NN: An efficient package for training and executing neural-network interatomic potentials
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September 2019
Stable Liquid Hydrogen at High Pressure by a Novel Ab Initio Molecular-Dynamics Calculation
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March 2008
Amp: A modular approach to machine learning in atomistic simulations
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October 2016
A new generation of effective core potentials for correlated calculations
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December 2017
Breaking the carbon dimer: The challenges of multiple bond dissociation with full configuration interaction quantum Monte Carlo methods
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August 2011
Kernel Methods for Pattern Analysis
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January 2011
Machine Learning of Analytical Electron Density in Large Molecules Through Message-Passing
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May 2021
Gaussian process based optimization of molecular geometries using statistically sampled energy surfaces from quantum Monte Carlo
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October 2018
Zero-Variance Principle for Monte Carlo Algorithms
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December 1999
Energy derivatives in quantum Monte Carlo involving the zero-variance property
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December 2008
Density Functional Theory of Electronic Structure
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January 1996
Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons
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April 2010
Accurate, Efficient, and Simple Forces Computed with Quantum Monte Carlo Methods
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January 2005
Accurate ab initio vibrational energies of methyl chloride
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June 2015
ReaxFF Reactive Force Field for Molecular Dynamics Simulations of Hydrocarbon Oxidation
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February 2008
Machine Learning Diffusion Monte Carlo Energies
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November 2022
Phonons of metallic hydrogen with quantum Monte Carlo
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January 2022
Accuracy of ab initio electron correlation and electron densities in vanadium dioxide
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November 2017
Coupled-cluster theory in quantum chemistry
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February 2007
Practical Schemes for Accurate Forces in Quantum Monte Carlo
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October 2014
Comprehending the quadruple bonding conundrum in C2 from excited state potential energy curves
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January 2020
Assessing the accuracy of quantum Monte Carlo and density functional theory for energetics of small water clusters
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June 2012
A Comparison of Automatic Differentiation and Continuous Sensitivity Analysis for Derivatives of Differential Equation Solutions
preprint
January 2018
Molecular force fields with gradient-domain machine learning: Construction and application to dynamics of small molecules with coupled cluster forces
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March 2019
A first-principles Quantum Monte Carlo study of two-dimensional (2D) GaSe
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October 2020
Energy-consistent pseudopotentials for quantum Monte Carlo calculations
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June 2007
P y SCF: the Python-based simulations of chemistry framework : The PySCF program
Sun, Qiming; Berkelbach, Timothy C.; Blunt, Nick S.
Wiley Interdisciplinary Reviews: Computational Molecular Science, Vol. 8, Issue 1
https://doi.org/10.1002/wcms.1340
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September 2017
Generalized Gradient Approximation Made Simple
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October 1996
QMCPACK : an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids
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April 2018
The self-interaction correction in the time domain
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November 2010
Enabling robust offline active learning for machine learning potentials using simple physics-based priors
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January 2021
Less is more: Sampling chemical space with active learning
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June 2018
Nodal Pulay terms for accurate diffusion quantum Monte Carlo forces
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February 2008
A structural optimization algorithm with stochastic forces and stresses
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November 2022
Total forces in the diffusion Monte Carlo method with nonlocal pseudopotentials
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July 2008
Zero-variance zero-bias principle for observables in quantum Monte Carlo: Application to forces
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November 2003
A new generation of effective core potentials from correlated calculations: 3d transition metal series
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October 2018
Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces
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April 2007
Transferable Machine-Learning Model of the Electron Density
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December 2018
Construction of high-dimensional neural network potentials using environment-dependent atom pairs
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May 2012