Comparing the accuracy of high-dimensional neural network potentials and the systematic molecular fragmentation method: A benchmark study for all-trans alkanes

Energy-Based Molecular Fragmentation Methods

(2015) Michael A. Collins et al.   CHEMICAL REVIEWS

Constructing high-dimensional neural network potentials: A tutorial review

(2015) Jörg Behler   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Communication: Rate coefficients of the H + CH4 → H2 + CH3 reaction from ring polymer molecular dynamics on a highly accurate potential energy surface

(2015) Qingyong Meng et al.   JOURNAL OF CHEMICAL PHYSICS

High-Dimensional Neural Network Potentials for Organic Reactions and an Improved Training Algorithm

(2015) Michael Gastegger et al.   Journal of Chemical Theory and Computation

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

The Combined Fragmentation and Systematic Molecular Fragmentation Methods

(2014) Michael A. Collins et al.   ACCOUNTS OF CHEMICAL RESEARCH

Fragment Quantum Mechanical Calculation of Proteins and Its Applications

(2014) Xiao He et al.   ACCOUNTS OF CHEMICAL RESEARCH

Next generation interatomic potentials for condensed systems

(2014) Christopher Michael Handley et al.   EUROPEAN PHYSICAL JOURNAL B

Representing potential energy surfaces by high-dimensional neural network potentials

(2014) J Behler   JOURNAL OF PHYSICS-CONDENSED MATTER

Permutation invariant polynomial neural network approach to fitting potential energy surfaces

(2013) Bin Jiang et al.   JOURNAL OF CHEMICAL PHYSICS

A Density-Functional Theory-Based Neural Network Potential for Water Clusters Including van der Waals Corrections

(2013) Tobias Morawietz et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Modified Feed-Forward Neural Network Structures and Combined-Function-Derivative Approximations Incorporating Exchange Symmetry for Potential Energy Surface Fitting

(2012) Hieu T. T. Nguyen et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Neural network potentials for metals and oxides - First applications to copper clusters at zinc oxide

(2012) Nongnuch Artrith et al.   PHYSICA STATUS SOLIDI B-BASIC SOLID STATE PHYSICS

Systematic fragmentation of large molecules by annihilation

(2012) Michael A. Collins   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

High-dimensional neural network potentials for metal surfaces: A prototype study for copper

(2012) Nongnuch Artrith et al.   PHYSICAL REVIEW B

Fragmentation Methods: A Route to Accurate Calculations on Large Systems

(2011) Mark S. Gordon et al.   CHEMICAL REVIEWS

An overlap fitted chain of spheres exchange method

(2011) Róbert Izsák et al.   JOURNAL OF CHEMICAL PHYSICS

Atom-centered symmetry functions for constructing high-dimensional neural network potentials

(2011) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations

(2011) Jörg Behler   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

The ORCA program system

(2011) Frank Neese   Wiley Interdisciplinary Reviews-Computational Molecular Science

Potential Energy Surfaces Fitted by Artificial Neural Networks

(2010) Chris M. Handley et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Accurate treatment of nonbonded interactions within systematic molecular fragmentation

(2009) Matthew A. Addicoat et al.   JOURNAL OF CHEMICAL PHYSICS

Simultaneous fitting of a potential-energy surface and its corresponding force fields using feedforward neural networks

(2009) A. Pukrittayakamee et al.   JOURNAL OF CHEMICAL PHYSICS

Efficient, approximate and parallel Hartree–Fock and hybrid DFT calculations. A ‘chain-of-spheres’ algorithm for the Hartree–Fock exchange

(2008) Frank Neese et al.   CHEMICAL PHYSICS

Optimized auxiliary basis sets for explicitly correlated methods

(2008) Kazim E. Yousaf et al.   JOURNAL OF CHEMICAL PHYSICS

Systematically convergent basis sets for explicitly correlated wavefunctions: The atoms H, He, B–Ne, and Al–Ar

(2008) Kirk A. Peterson et al.   JOURNAL OF CHEMICAL PHYSICS

Metadynamics Simulations of the High-Pressure Phases of Silicon Employing a High-Dimensional Neural Network Potential

(2008) Jörg Behler et al.   PHYSICAL REVIEW LETTERS