Publications

Y. Kim, J. Heiland (2023). Convolutional Autoencoders, Clustering, and POD for Low-dimensional Parametrization of Navier-Stokes Equations.
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P. Benner, P. Goyal, J. Heiland, I. Pontes (2023). A quadratic decoder approach to nonintrusive reduced-order modeling of nonlinear dynamical systems. Proceedings in Applied Mathematics & Mechanics.
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Peter Benner, Jan Heiland, Steffen W. R. Werner (2023). A low-rank solution method for Riccati equations with indefinite quadratic terms. Numerical Algorithms.
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Peter Benner, Jan Heiland, Steffen W. R. Werner (2022). Robust output-feedback stabilization for incompressible flows using low-dimensional (ℋ)(_mbox(ınfty) )-controllers. Comput. Optim. Appl..
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Peter Benner, Pawan Goyal, Jan Heiland, Igor Pontes Duff (2022). Operator Inference and Physics-Informed Learning of Low-Dimensional Models for Incompressible Flows. Electron. Trans. Numer. Anal..
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Jan Heiland, Benjamin Unger (2022). Identification of Linear Time-Invariant Systems with Dynamic Mode Decomposition. MDPI Mathematics.
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Jan Heiland, Peter Benner, Rezvan Bahmani (2022). Convolutional Neural Networks for Very Low-Dimensional LPV Approximations of Incompressible Navier-Stokes Equations. Frontiers Appl. Math. Stat..
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Jan Heiland, Yongho Kim (2022). Convolutional Autoencoders and Clustering for Low-dimensional Parametrization of Incompressible Flows. IFAC-PapersOnLine.
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Jan Heiland (2022). Convergence of Coprime Factor Perturbations for Robust Stabilization of Oseen Systems. Math. Control Relat. Fields.
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Peter Benner, Pawan Goyal, Jan Heiland, Igor Pontes (2022). A quadratic decoder approach to nonintrusive reduced-order modeling of nonlinear dynamical systems.
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