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Stefan Chmiela

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From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields

Sep 21, 2023
J. Thorben Frank, Oliver T. Unke, Klaus-Robert Müller, Stefan Chmiela

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Reconstructing Kernel-based Machine Learning Force Fields with Super-linear Convergence

Dec 24, 2022
Stefan Blücher, Klaus-Robert Müller, Stefan Chmiela

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Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields

Aug 25, 2022
Niklas Frederik Schmitz, Klaus-Robert Müller, Stefan Chmiela

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Detect the Interactions that Matter in Matter: Geometric Attention for Many-Body Systems

Jun 14, 2021
Thorben Frank, Stefan Chmiela

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BIGDML: Towards Exact Machine Learning Force Fields for Materials

Jun 08, 2021
Huziel E. Sauceda, Luis E. Gálvez-González, Stefan Chmiela, Lauro Oliver Paz-Borbón, Klaus-Robert Müller, Alexandre Tkatchenko

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SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects

May 01, 2021
Oliver T. Unke, Stefan Chmiela, Michael Gastegger, Kristof T. Schütt, Huziel E. Sauceda, Klaus-Robert Müller

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Machine Learning Force Fields

Oct 14, 2020
Oliver T. Unke, Stefan Chmiela, Huziel E. Sauceda, Michael Gastegger, Igor Poltavsky, Kristof T. Schütt, Alexandre Tkatchenko, Klaus-Robert Müller

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Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach

May 04, 2020
Jiang Wang, Stefan Chmiela, Klaus-Robert Müller, Frank Noè, Cecilia Clementi

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SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

Dec 19, 2017
Kristof T. Schütt, Pieter-Jan Kindermans, Huziel E. Sauceda, Stefan Chmiela, Alexandre Tkatchenko, Klaus-Robert Müller

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