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

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

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

SchNet – A deep learning architecture for molecules and materials

(2018) K. T. Schütt 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

Toward Accurate Conformational Energies of Smaller Peptides and Medium-Sized Macrocycles: MPCONF196 Benchmark Energy Data Set

(2018) Jan Řezáč et al.   Journal of Chemical Theory and Computation

Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network

(2018) Jon Paul Janet et al.   Journal of Physical Chemistry Letters

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

(2018) Kun Yao et al.   Chemical Science

Improving solvation energy predictions using the SMD solvation method and semiempirical electronic structure methods

(2018) Jimmy C. Kromann et al.   JOURNAL OF CHEMICAL PHYSICS

Transferability in Machine Learning for Electronic Structure via the Molecular Orbital Basis

(2018) Matthew Welborn et al.   Journal of Chemical Theory and Computation

Discovering a Transferable Charge Assignment Model Using Machine Learning

(2018) Andrew E. Sifain et al.   Journal of Physical Chemistry Letters

Machine learning for molecular and materials science

(2018) Keith T. Butler et al.   NATURE

Planning chemical syntheses with deep neural networks and symbolic AI

(2018) Marwin H. S. Segler et al.   NATURE

Inverse molecular design using machine learning: Generative models for matter engineering

(2018) Benjamin Sanchez-Lengeling et al.   SCIENCE

A Density Functional Tight Binding Layer for Deep Learning of Chemical Hamiltonians

(2018) Haichen Li et al.   Journal of Chemical Theory and Computation

A Comparison of Quantum and Molecular Mechanical Methods to Estimate Strain Energy in Druglike Fragments

(2017) Benjamin D. Sellers et al.   Journal of Chemical Information and Modeling

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

Machine learning of accurate energy-conserving molecular force fields

(2017) Stefan Chmiela et al.   Science Advances

Minimal Basis Iterative Stockholder: Atoms in Molecules for Force-Field Development

(2016) Toon Verstraelen et al.   Journal of Chemical Theory and Computation

The S66x8 benchmark for noncovalent interactions revisited: explicitly correlated ab initio methods and density functional theory

(2016) Brina Brauer et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

(2012) Matthias Rupp et al.   PHYSICAL REVIEW LETTERS

An overlap fitted chain of spheres exchange method

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

The ORCA program system

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