Manifolds of quasi-constant SOAP and ACSF fingerprints and the resulting failure to machine learn four-body interactions

Machine learning potentials for extended systems: a perspective

(2021) Jörg Behler et al.   EUROPEAN PHYSICAL JOURNAL B

FCHL revisited: Faster and more accurate quantum machine learning

(2020) Anders S. Christensen et al.   JOURNAL OF CHEMICAL PHYSICS

The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules

(2020) Justin S. Smith et al.   Scientific Data

Gaussian representation for image recognition and reinforcement learning of atomistic structure

(2020) Mads-Peter V. Christiansen et al.   JOURNAL OF CHEMICAL PHYSICS

Quantum machine learning using atom-in-molecule-based fragments selected on the fly

(2020) Bing Huang et al.   Nature Chemistry

Incompleteness of Atomic Structure Representations

(2020) Sergey N. Pozdnyakov et al.   PHYSICAL REVIEW LETTERS

A novel approach to describe chemical environments in high-dimensional neural network potentials

(2019) Emir Kocer et al.   JOURNAL OF CHEMICAL PHYSICS

Iterative-Learning Strategy for the Development of Application-Specific Atomistic Force Fields

(2019) Tran Doan Huan et al.   Journal of Physical Chemistry C

wACSF—Weighted atom-centered symmetry functions as descriptors in machine learning potentials

(2018) M. Gastegger et al.   JOURNAL OF CHEMICAL PHYSICS

Solid harmonic wavelet scattering for predictions of molecule properties

(2018) Michael Eickenberg et al.   JOURNAL OF CHEMICAL PHYSICS

Machine Learning Adaptive Basis Sets for Efficient Large Scale DFT Simulation

(2018) Ole Schütt et al.   Journal of Chemical Theory and Computation

Spherical harmonics based descriptor for neural network potentials: Structure and dynamics of Au147 nanocluster

(2017) Shweta Jindal et al.   JOURNAL OF CHEMICAL PHYSICS

A fingerprint based metric for measuring similarities of crystalline structures

(2016) Li Zhu et al.   JOURNAL OF CHEMICAL PHYSICS

Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials

(2016) Alexander V. Shapeev   MULTISCALE MODELING & SIMULATION

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

(2015) A.P. Thompson et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Machine Learning for Quantum Mechanical Properties of Atoms in Molecules

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

Metrics for measuring distances in configuration spaces

(2013) Ali Sadeghi et al.   JOURNAL OF CHEMICAL PHYSICS

On representing chemical environments

(2013) Albert P. Bartók et al.   PHYSICAL REVIEW B

Comment on “Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning”

(2012) Jonathan E. Moussa   PHYSICAL REVIEW LETTERS

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

(2012) Matthias Rupp et al.   PHYSICAL REVIEW LETTERS

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

(2011) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS