Dynamical Systems (math.DS)

Data-driven identification of latent port-Hamiltonian systems
A data-driven framework for the identification of latent port-Hamiltonian systems
Johannes Rettberg, Jonas Kneifl, Julius Herb, Patrick Buchfink, Jörg Fehr, Bernard Haasdonk
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Data-driven identification of latent port-Hamiltonian systems
VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification
The proposed framework discovers probabilistic governing equations from high-dimensional data in a low-dimensional latent space
Paolo Conti, Jonas Kneifl, Andrea Manzoni, Attilio Frangi, Jörg Fehr, Steven L. Brunton, J. Nathan Kutz
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VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification
Multi-Hierarchical Surrogate Learning for Structural Dynamical Crash Simulations Using Graph Convolutional Neural Networks
Crash simulations play an essential role in improving vehicle safety, design optimization, and injury risk estimation. Unfortunately, …
Jonas Kneifl, Jörg Fehr, Steven L. Brunton, J. Nathan Kutz
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Multi-Hierarchical Surrogate Learning for Structural Dynamical Crash Simulations Using Graph Convolutional Neural Networks