AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials

Approaches for machine learning intermolecular interaction energies and application to energy components from symmetry adapted perturbation theory

(2020) Derek P. Metcalf et al.   JOURNAL OF CHEMICAL PHYSICS

Classical Pauli repulsion: An anisotropic, atomic multipole model

(2019) Joshua A. Rackers et al.   JOURNAL OF CHEMICAL PHYSICS

PhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments, and Partial Charges

(2019) Oliver T. Unke et al.   Journal of Chemical Theory and Computation

Deep Learning in Chemistry

(2019) Adam C. Mater et al.   Journal of Chemical Information and Modeling

Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning

(2019) Justin S. Smith et al.   Nature Communications

A Machine Learning Approach for Prediction of Rate Constants

(2019) Paul L. Houston et al.   Journal of Physical Chemistry Letters

Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network

(2019) Roman Zubatyuk et al.   Science Advances

Recent developments in symmetry‐adapted perturbation theory

(2019) Konrad Patkowski   Wiley Interdisciplinary Reviews-Computational Molecular Science

Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

(2018) Tristan Bereau et al.   JOURNAL OF CHEMICAL PHYSICS

Hierarchical modeling of molecular energies using a deep neural network

(2018) Nicholas Lubbers et al.   JOURNAL OF CHEMICAL PHYSICS

SchNet – A deep learning architecture for molecules and materials

(2018) K. T. Schütt et al.   JOURNAL OF CHEMICAL PHYSICS

Guest Editorial: Special Topic on Data-Enabled Theoretical Chemistry

(2018) Matthias Rupp et al.   JOURNAL OF CHEMICAL PHYSICS

Less is more: Sampling chemical space with active learning

(2018) Justin S. Smith et al.   JOURNAL OF CHEMICAL PHYSICS

New Angles on Standard Force Fields: Toward a General Approach for Treating Atomic-Level Anisotropy

(2018) Mary J. Van Vleet et al.   Journal of Chemical Theory and Computation

AMOEBA Polarizable Atomic Multipole Force Field for Nucleic Acids

(2018) Changsheng Zhang et al.   Journal of Chemical Theory and Computation

The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics

(2018) Kun Yao et al.   Chemical Science

A physically grounded damped dispersion model with particle mesh Ewald summation

(2018) Joshua A. Rackers et al.   JOURNAL OF CHEMICAL PHYSICS

Improvements to the AMOEBA Force Field by Introducing Anisotropic Atomic Polarizability of the Water Molecule

(2018) Akshaya K. Das et al.   Journal of Chemical Theory and Computation

Chemical shifts in molecular solids by machine learning

(2018) Federico M. Paruzzo et al.   Nature Communications

The BioFragment Database (BFDb): An open-data platform for computational chemistry analysis of noncovalent interactions

(2017) Lori A. Burns et al.   JOURNAL OF CHEMICAL PHYSICS

Improving the accuracy of Møller-Plesset perturbation theory with neural networks

(2017) Robert T. McGibbon et al.   JOURNAL OF CHEMICAL PHYSICS

An optimized charge penetration model for use with the AMOEBA force field

(2017) Joshua A. Rackers et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

(2017) J. S. Smith et al.   Chemical Science

Quantum-chemical insights from deep tensor neural networks

(2017) Kristof T. Schütt et al.   Nature Communications

Machine learning of accurate energy-conserving molecular force fields

(2017) Stefan Chmiela et al.   Science Advances

Next-Generation Force Fields from Symmetry-Adapted Perturbation Theory

(2016) Jesse G. McDaniel et al.   Annual Review of Physical Chemistry

Beyond Born–Mayer: Improved Models for Short-Range Repulsion in ab Initio Force Fields

(2016) Mary J. Van Vleet et al.   Journal of Chemical Theory and Computation

Toward a Physically Motivated Force Field: Hydrogen Bond Directionality from a Symmetry-Adapted Perturbation Theory Perspective

(2016) Maxim Tafipolsky et al.   Journal of Chemical Theory and Computation

The Cambridge Structural Database

(2016) Colin R. Groom et al.   Acta Crystallographica Section B-Structural Science Crystal Engineering and Materials

OPLS3: A Force Field Providing Broad Coverage of Drug-like Small Molecules and Proteins

(2015) Edward Harder et al.   Journal of Chemical Theory and Computation

Transferable Atomic Multipole Machine Learning Models for Small Organic Molecules

(2015) Tristan Bereau et al.   Journal of Chemical Theory and Computation

Spatial assignment of symmetry adapted perturbation theory interaction energy components: The atomic SAPT partition

(2014) Robert M. Parrish et al.   JOURNAL OF CHEMICAL PHYSICS

Levels of symmetry adapted perturbation theory (SAPT). I. Efficiency and performance for interaction energies

(2014) Trent M. Parker et al.   JOURNAL OF CHEMICAL PHYSICS

Chemical Assignment of Symmetry-Adapted Perturbation Theory Interaction Energy Components: The Functional-Group SAPT Partition

(2014) Robert M. Parrish et al.   Journal of Chemical Theory and Computation

Physically-Motivated Force Fields from Symmetry-Adapted Perturbation Theory

(2013) Jesse G. McDaniel et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Construction of high-dimensional neural network potentials using environment-dependent atom pairs

(2012) K. V. Jovan Jose et al.   JOURNAL OF CHEMICAL PHYSICS

Large-scale symmetry-adapted perturbation theory computations via density fitting and Laplace transformation techniques: Investigating the fundamental forces of DNA-intercalator interactions

(2011) Edward G. Hohenstein et al.   JOURNAL OF CHEMICAL PHYSICS

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

(2011) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

S66: A Well-balanced Database of Benchmark Interaction Energies Relevant to Biomolecular Structures

(2011) Jan Řezáč et al.   Journal of Chemical Theory and Computation

Symmetry-adapted perturbation theory of intermolecular forces

(2011) Krzysztof Szalewicz   Wiley Interdisciplinary Reviews-Computational Molecular Science

Density fitting and Cholesky decomposition approximations in symmetry-adapted perturbation theory: Implementation and application to probe the nature of π-π interactions in linear acenes

(2010) Edward G. Hohenstein et al.   JOURNAL OF CHEMICAL PHYSICS

A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu

(2010) Stefan Grimme et al.   JOURNAL OF CHEMICAL PHYSICS

CHARMM: The biomolecular simulation program

(2009) B. R. Brooks et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY