Stefan Chmiela
Orcid: 0000-0003-0892-952X
According to our database1,
Stefan Chmiela authored at least 13 papers
between 2017 and 2026.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on id.loc.gov
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on d-nb.info
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Bibliography
2026
Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics.
CoRR, January, 2026
2025
Atomic orbits in molecules and materials for improving machine learning force fields.
Mach. Learn. Sci. Technol., 2025
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025
2024
Euclidean Fast Attention: Machine Learning Global Atomic Representations at Linear Cost.
CoRR, 2024
2023
Trans. Mach. Learn. Res., 2023
From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields.
CoRR, 2023
2022
Reconstructing Kernel-based Machine Learning Force Fields with Super-linear Convergence.
CoRR, 2022
Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields.
CoRR, 2022
2021
Detect the Interactions that Matter in Matter: Geometric Attention for Many-Body Systems.
CoRR, 2021
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects.
CoRR, 2021
2019
sGDML: Constructing accurate and data efficient molecular force fields using machine learning.
Comput. Phys. Commun., 2019
2017
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017