Metadynamics for training neural network model chemistries: A competitive assessment

Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems

(2018) Andrea Grisafi et al.   PHYSICAL REVIEW LETTERS

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

(2018) Kun Yao et al.   Chemical Science

Is Multitask Deep Learning Practical for Pharma?

(2017) Bharath Ramsundar et al.   Journal of Chemical Information and Modeling

The many-body expansion combined with neural networks

(2017) Kun Yao et al.   JOURNAL OF CHEMICAL PHYSICS

Toward chemical accuracy in the description of ion–water interactions through many-body representations. Alkali-water dimer potential energy surfaces

(2017) Marc Riera et al.   JOURNAL OF CHEMICAL PHYSICS

Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure–Property Relationships

(2017) Jon Paul Janet et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Molecular Origin of the Vibrational Structure of Ice Ih

(2017) Daniel R. Moberg et al.   Journal of Physical Chemistry Letters

Intrinsic Bond Energies from a Bonds-in-Molecules Neural Network

(2017) Kun Yao et al.   Journal of Physical Chemistry Letters

Accurate Neural Network Description of Surface Phonons in Reactive Gas–Surface Dynamics: N2 + Ru(0001)

(2017) Khosrow Shakouri et al.   Journal of Physical Chemistry Letters

Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

(2017) Nicholas J. Browning et al.   Journal of Physical Chemistry Letters

Material discovery by combining stochastic surface walking global optimization with a neural network

(2017) Si-Da Huang et al.   Chemical Science

Predicting electronic structure properties of transition metal complexes with neural networks

(2017) Jon Paul Janet et al.   Chemical Science

Machine learning molecular dynamics for the simulation of infrared spectra

(2017) Michael Gastegger et al.   Chemical Science

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

Bypassing the Kohn-Sham equations with machine learning

(2017) Felix Brockherde et al.   Nature Communications

ANI-1, A data set of 20 million calculated off-equilibrium conformations for organic molecules

(2017) Justin S. Smith et al.   Scientific Data

Machine learning of accurate energy-conserving molecular force fields

(2017) Stefan Chmiela et al.   Science Advances

Enhancing Important Fluctuations: Rare Events and Metadynamics from a Conceptual Viewpoint

(2016) Omar Valsson et al.   Annual Review of Physical Chemistry

On the accuracy of the MB-pol many-body potential for water: Interaction energies, vibrational frequencies, and classical thermodynamic and dynamical properties from clusters to liquid water and ice

(2016) Sandeep K. Reddy et al.   JOURNAL OF CHEMICAL PHYSICS

Kinetic Energy of Hydrocarbons as a Function of Electron Density and Convolutional Neural Networks

(2016) Kun Yao et al.   Journal of Chemical Theory and Computation

Ab Initio Investigation of O–H Dissociation from the Al–OH2 Complex Using Molecular Dynamics and Neural Network Fitting

(2016) Thi H. Ho et al.   JOURNAL OF PHYSICAL CHEMISTRY A

How van der Waals interactions determine the unique properties of water

(2016) Tobias Morawietz et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints

(2015) Olexandr Isayev et al.   CHEMISTRY OF MATERIALS

Understanding machine-learned density functionals

(2015) Li Li et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Understanding kernel ridge regression: Common behaviors from simple functions to density functionals

(2015) Kevin Vu et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Constructing high-dimensional neural network potentials: A tutorial review

(2015) Jörg Behler   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

On the representation of many-body interactions in water

(2015) Gregory R. Medders et al.   JOURNAL OF CHEMICAL PHYSICS

Machine-Learning-Augmented Chemisorption Model for CO2 Electroreduction Catalyst Screening

(2015) Xianfeng Ma et al.   Journal of Physical Chemistry Letters

Machine Learning for Quantum Mechanical Properties of Atoms in Molecules

(2015) Matthias Rupp et al.   Journal of Physical Chemistry Letters

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

(2015) Katja Hansen et al.   Journal of Physical Chemistry Letters

Neural network-based approaches for building high dimensional and quantum dynamics-friendly potential energy surfaces

(2014) Sergei Manzhos et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Advances in molecular quantum chemistry contained in the Q-Chem 4 program package

(2014) Yihan Shao et al.   MOLECULAR PHYSICS

Stochastic surface walking method for crystal structure and phase transition pathway prediction

(2014) Cheng Shang et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Modeling electronic quantum transport with machine learning

(2014) Alejandro Lopez-Bezanilla et al.   PHYSICAL REVIEW B

How to represent crystal structures for machine learning: Towards fast prediction of electronic properties

(2014) K. T. Schütt et al.   PHYSICAL REVIEW B

Quantum chemistry structures and properties of 134 kilo molecules

(2014) Raghunathan Ramakrishnan et al.   Scientific Data

Lead candidates for high-performance organic photovoltaics from high-throughput quantum chemistry – the Harvard Clean Energy Project

(2013) Johannes Hachmann et al.   Energy & Environmental Science

Orbital-free bond breaking via machine learning

(2013) John C. Snyder et al.   JOURNAL OF CHEMICAL PHYSICS

A Critical Assessment of Two-Body and Three-Body Interactions in Water

(2013) Gregory R. Medders et al.   Journal of Chemical Theory and Computation

Stochastic Surface Walking Method for Structure Prediction and Pathway Searching

(2013) Cheng Shang et al.   Journal of Chemical Theory and Computation

Accelerating materials property predictions using machine learning

(2013) Ghanshyam Pilania et al.   Scientific Reports

Finding Density Functionals with Machine Learning

(2012) John C. Snyder et al.   PHYSICAL REVIEW LETTERS

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

(2012) Matthias Rupp et al.   PHYSICAL REVIEW LETTERS

Accelerated computational discovery of high-performance materials for organic photovoltaics by means of cheminformatics

(2011) Roberto Olivares-Amaya et al.   Energy & Environmental Science

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

(2011) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid

(2011) Johannes Hachmann et al.   Journal of Physical Chemistry Letters

Nucleation mechanism for the direct graphite-to-diamond phase transition

(2011) Rustam Z. Khaliullin et al.   NATURE MATERIALS

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

(2011) Jörg Behler   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide

(2011) Nongnuch Artrith et al.   PHYSICAL REVIEW B

Metadynamics

(2011) Alessandro Barducci et al.   Wiley Interdisciplinary Reviews-Computational Molecular Science

Tautomerism in Reduced Pyrazinacenes

(2010) Roberto Scipioni et al.   Journal of Chemical Theory and Computation

Fitting sparse multidimensional data with low-dimensional terms

(2009) Sergei Manzhos et al.   COMPUTER PHYSICS COMMUNICATIONS

Theoretical Analysis of the Possible Intermediates in the Formation of [W6O19]2–

(2009) Laia Vilà-Nadal et al.   EUROPEAN JOURNAL OF INORGANIC CHEMISTRY

“Mindless” DFT Benchmarking

(2009) Martin Korth et al.   Journal of Chemical Theory and Computation

Free Energy Barriers for the N-Terminal Asparagine to Succinimide Conversion: Quantum Molecular Dynamics Simulations for the Fully Solvated Model

(2009) Ilya Kaliman et al.   Journal of Chemical Theory and Computation

First-principles simulations of hydrogen peroxide formation catalyzed by small neutral gold clusters

(2009) Katarzyna A. Kacprzak et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Ab initiostudy of the diffusion and decomposition pathways ofSiHxspecies on Si(100)

(2009) Michele Ceriotti et al.   PHYSICAL REVIEW B

Conformational Behavior of Cinchonidine Revisited: A Combined Theoretical and Experimental Study

(2008) Atsushi Urakawa et al.   JOURNAL OF PHYSICAL CHEMISTRY A

First-Principles Molecular Dynamics Study of the Heterogeneous Reduction of NO2 on Soot Surfaces

(2008) Antonio Rodríguez-Fortea et al.   Journal of Physical Chemistry C

Molecular Dynamics Prediction of the Mechanism of Ester Hydrolysis in Water

(2008) Hakan Gunaydin et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Long-range corrected hybrid density functionals with damped atom–atom dispersion corrections

(2008) Jeng-Da Chai et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS