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Paul J. Atzberger

Geometric Neural Operators (GNPs) for Data-Driven Deep Learning of Non-Euclidean Operators

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Apr 16, 2024
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SDYN-GANs: Adversarial Learning Methods for Multistep Generative Models for General Order Stochastic Dynamics

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Feb 07, 2023
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GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions

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Jun 10, 2022
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MLMOD Package: Machine Learning Methods for Data-Driven Modeling in LAMMPS

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Jul 29, 2021
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Variational Autoencoders for Learning Nonlinear Dynamics of Physical Systems

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Dec 07, 2020
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GMLS-Nets: A framework for learning from unstructured data

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Sep 13, 2019
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Importance of the Mathematical Foundations of Machine Learning Methods for Scientific and Engineering Applications

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Aug 07, 2018
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