77 citations · 95 across the 4 of their papers we have counts for
4 papers
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular Dynamics
Mathias Schreiner, Ole Winther, Simon Olsson
Computing properties of molecular systems rely on estimating expectations of the (unnormalized) Boltzmann distribution. Molecular dynamics (MD) is a broadly adopted technique to ap…
Transition1x -- a Dataset for Building Generalizable Reactive Machine Learning Potentials
Mathias Schreiner, Arghya Bhowmik, Tejs Vegge +2
Machine Learning (ML) models have, in contrast to their usefulness in molecular dynamics studies, had limited success as surrogate potentials for reaction barrier search. It is due…
NeuralNEB -- Neural Networks can find Reaction Paths Fast
Mathias Schreiner, Arghya Bhowmik, Tejs Vegge +2
Quantum mechanical methods like Density Functional Theory (DFT) are used with great success alongside efficient search algorithms for studying kinetics of reactive systems. However…
Catalogue of new Herbig Ae/Be and classical Be stars. A machine learning approach to Gaia DR2
M. Vioque, R. D. Oudmaijer, M. Schreiner +4
The intermediate-mass pre-main sequence Herbig Ae/Be stars are key to understanding the differences in formation mechanisms between low- and high-mass stars. The study of the gener…