Using principal component analysis for neural network high-dimensional potential energy surface

Machine Learning for Molecular Simulation

(2020) Frank Noé et al.   Annual Review of Physical Chemistry

SchNet – A deep learning architecture for molecules and materials

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

A reactive, scalable, and transferable model for molecular energies from a neural network approach based on local information

(2018) Oliver T. Unke et al.   JOURNAL OF CHEMICAL PHYSICS

Keto–enol tautomerism in micro-hydrated acetylacetone: an atoms-in-molecules study

(2018) Bastien Casier et al.   THEORETICAL CHEMISTRY ACCOUNTS

Quantum-chemical insights from deep tensor neural networks

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

Perspective: Machine learning potentials for atomistic simulations

(2016) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

Principal component analysis: a review and recent developments

(2016) Ian T. Jolliffe et al.   PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Machine learning exciton dynamics

(2016) Florian Häse et al.   Chemical Science

Machine learning for quantum mechanics in a nutshell

(2015) Matthias Rupp   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Probing keto–enol tautomerism using photoelectron spectroscopy

(2015) Nathalie Capron et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Machine learning of molecular electronic properties in chemical compound space

(2013) Grégoire Montavon et al.   NEW JOURNAL OF PHYSICS

Theoretical study of keto-enol tautomerism by quantum mechanical calculations (the QM/MC/FEP method)

(2012) Thanayuth Kaweetirawatt et al.   JOURNAL OF PHYSICAL ORGANIC CHEMISTRY

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

(2012) Matthias Rupp et al.   PHYSICAL REVIEW LETTERS

Coordinate reduction for exploring chemical reaction paths

(2012) Adam B. Birkholz et al.   THEORETICAL CHEMISTRY ACCOUNTS

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

(2011) Jörg Behler   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Potential Energy Surfaces Fitted by Artificial Neural Networks

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