275 citations · 652 across the 8 of their papers we have counts for
8 papers
Uncertainty-aware electronic density-functional distributions
Teitur Hansen, Jens Jørgen Mortensen, Thomas Bligaard +1
We introduce a method for the estimation of uncertainties in density-functional-theory (DFT) calculations for atomistic systems. The method is based on the construction of an uncer…
GPAW: An open Python package for electronic-structure calculations
Jens Jørgen Mortensen, Ask Hjorth Larsen, Mikael Kuisma +44
We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density…
Machine-learning enabled optimization of atomic structures using atoms with fractional existence
Casper Larsen, Sami Kaappa, Andreas Lynge Vishart +2
We introduce a method for global optimization of the structure of atomic systems that uses additional atoms with fractional existence. The method allows for movement of atoms over…
Machine Learning with bond information for local structure optimizations in surface science
Estefanía Garijo del Río, Sami Kaappa, José A. Garrido Torres +2
Local optimization of adsorption systems inherently involves different scales: within the substrate, within the molecule, and between molecule and substrate. In this work, we show…
An Atomistic Machine Learning Package for Surface Science and Catalysis
Martin Hangaard Hansen, José A. Garrido Torres, Paul C. Jennings +4
We present work flows and a software module for machine learning model building in surface science and heterogeneous catalysis. This includes fingerprinting atomic structures from…
Low-Scaling Algorithm for Nudged Elastic Band Calculations Using a Surrogate Machine Learning Model
José A. Garrido Torres, Paul C. Jennings, Martin H. Hansen +2
We present the incorporation of a surrogate Gaussian Process Regression (GPR) atomistic model to greatly accelerate the rate of convergence of classical Nudged Elastic Band (NEB) c…