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Stefan Chmiela

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

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Sep 21, 2023
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Reconstructing Kernel-based Machine Learning Force Fields with Super-linear Convergence

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Dec 24, 2022
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Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields

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Aug 25, 2022
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Detect the Interactions that Matter in Matter: Geometric Attention for Many-Body Systems

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Jun 14, 2021
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BIGDML: Towards Exact Machine Learning Force Fields for Materials

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Jun 08, 2021
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SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects

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May 01, 2021
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Machine Learning Force Fields

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Oct 14, 2020
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Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach

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May 04, 2020
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SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

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Dec 19, 2017
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