Stefan Chmiela

Scopus Author ID ORCID

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 14

Top Topics

Machine Learning

Single Molecule

Molecular Dynamics

Top Venues

Nature communications

Science advances

The Journal of chemical physics

The journal of physical chemistry letters

This page only lists publications with an associated author ORCID identifier.

Publications

J Thorben Frank, Oliver T Unke, Klaus-Robert Müller, Stefan Chmiela
A Euclidean transformer for fast and stable machine learned force fields. Nature communications 15 (1) (2024)
J Thorben Frank, Oliver T Unke, Klaus-Robert Müller, Stefan Chmiela
A Euclidean transformer for fast and stable machine learned force fields. Nature communications 15 (1) (2024)
J Thorben Frank, Oliver T Unke, Klaus-Robert Müller, Stefan Chmiela
A Euclidean transformer for fast and stable machine learned force fields. Nature communications 15 (1) (2024)
Stefan Chmiela, Valentin Vassilev-Galindo, Oliver T Unke, Adil M Kabylda, Huziel E Sauceda, Alexandre Tkatchenko, Klaus-Robert Müller
Accurate global machine learning force fields for molecules with hundreds of atoms. Science advances 9 (2) (2023)
Stefan Chmiela, Valentin Vassilev-Galindo, Oliver T Unke, Adil M Kabylda, Huziel E Sauceda, Alexandre Tkatchenko, Klaus-Robert Müller
Accurate global machine learning force fields for molecules with hundreds of atoms. Science advances 9 (2) (2023)
Adil Kabylda, Valentin Vassilev-Galindo, Stefan Chmiela, Igor Poltavsky, Alexandre Tkatchenko
Efficient interatomic descriptors for accurate machine learning force fields of extended molecules. Nature communications 14 (1) (2023)
Adil Kabylda, Valentin Vassilev-Galindo, Stefan Chmiela, Igor Poltavsky, Alexandre Tkatchenko
Author Correction: Efficient interatomic descriptors for accurate machine learning force fields of extended molecules. Nature communications 14 (1) (2023)
Stefan Blücher, Klaus-Robert Müller, Stefan Chmiela
Reconstructing Kernel-Based Machine Learning Force Fields with Superlinear Convergence. Journal of chemical theory and computation (2023)
Niklas Frederik Schmitz, Klaus-Robert Müller, Stefan Chmiela
Algorithmic Differentiation for Automated Modeling of Machine Learned Force Fields. The journal of physical chemistry letters 13 (43) (2022)
Huziel E Sauceda, Luis E Gálvez-González, Stefan Chmiela, Lauro Oliver Paz-Borbón, Klaus-Robert Müller, Alexandre Tkatchenko
BIGDML-Towards accurate quantum machine learning force fields for materials. Nature communications 13 (1) (2022)
Huziel E Sauceda, Valentin Vassilev-Galindo, Stefan Chmiela, Klaus-Robert Müller, Alexandre Tkatchenko
Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature. Nature communications 12 (1) (2021)
Oliver T Unke, Stefan Chmiela, Michael Gastegger, Kristof T Schütt, Huziel E Sauceda, Klaus-Robert Müller
SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects. Nature communications 12 (1) (2021)
Huziel E Sauceda, Michael Gastegger, Stefan Chmiela, Klaus-Robert Müller, Alexandre Tkatchenko
Molecular force fields with gradient-domain machine learning (GDML): Comparison and synergies with classical force fields. The Journal of chemical physics 153 (12) (2020)
Huziel E Sauceda, Stefan Chmiela, Igor Poltavsky, Klaus-Robert Müller, Alexandre Tkatchenko
Molecular force fields with gradient-domain machine learning: Construction and application to dynamics of small molecules with coupled cluster forces. The Journal of chemical physics 150 (11) (2019)