Large-Scale Computation of ℒ∞-Norms by a Greedy Subspace Method. - Nicat Aliyev; Peter Benner; Emre Mengi; Paul Schwerdtner; Matthias Voigt (SIAM J. Matrix Anal. Appl., 2017)

H-Infinity Loop-Shaped Model Predictive Control with Heat Pump Application. - Scott A. Bortoff; Paul Schwerdtner; Claus Danielson; Stefano Di Cairano (ECC, 2019)

Projection-Based Anti-Windup for Multivariable Control with Heat Pump Application. - Paul Schwerdtner; Scott A. Bortoff; Claus Danielson; Stefano Di Cairano (ECC, 2019)

Structure-Preserving Model Reduction for Dissipative Mechanical Systems. - Rebekka S. Beddig; Peter Benner; Ines Dorschky; Timo Reis; Paul Schwerdtner; Matthias Voigt; Steffen W. R. Werner (CoRR, 2020)

Risk Assessment for Machine Learning Models. - Paul Schwerdtner; Florens Greßner; Nikhil Kapoor; Felix Assion; René Sass; Wiebke Günther; Fabian Hüger; Peter Schlicht (CoRR, 2020)

Structure Preserving Model Order Reduction by Parameter Optimization. - Paul Schwerdtner; Matthias Voigt (CoRR, 2020)

Port-Hamiltonian System Identification from Noisy Frequency Response Data. - Paul Schwerdtner (CoRR, 2021)

Adaptive Sampling for Structure Preserving Model Order Reduction of Port-Hamiltonian Systems. - Paul Schwerdtner; Matthias Voigt (CoRR, 2021)

Structure-Preserving Model Order Reduction for Index One Port-Hamiltonian Descriptor Systems. - Paul Schwerdtner; Tim Moser; Volker Mehrmann; Matthias Voigt (CoRR, 2022)

Structure-Preserving Model Order Reduction for Index Two Port-Hamiltonian Descriptor Systems. - Tim Moser; Paul Schwerdtner; Volker Mehrmann; Matthias Voigt (CoRR, 2022)

H-Infinity Loop-Shaped Model Predictive Control With HVAC Application. - Scott A. Bortoff; Paul Schwerdtner; Claus Danielson; Stefano Di Cairano; Daniel J. Burns (IEEE Trans. Control. Syst. Technol., 2022)

SOBMOR: Structured Optimization-Based Model Order Reduction. - Paul Schwerdtner; Matthias Voigt (SIAM J. Sci. Comput., 2023)

Fixed-order H-infinity controller design for port-Hamiltonian systems. - Paul Schwerdtner; Matthias Voigt (Autom., 2023)

Optimization-based model order reduction of port-Hamiltonian descriptor systems. - Paul Schwerdtner; Tim Moser; Volker Mehrmann; Matthias Voigt (Syst. Control. Lett., 2023)

Greedy construction of quadratic manifolds for nonlinear dimensionality reduction and nonlinear model reduction. - Paul Schwerdtner; Benjamin Peherstorfer (CoRR, 2024)

Online learning of quadratic manifolds from streaming data for nonlinear dimensionality reduction and nonlinear model reduction. - Paul Schwerdtner; Prakash Mohan 004; Aleksandra Pachalieva; Julie Bessac; Daniel O'Malley; Benjamin Peherstorfer (CoRR, 2024)

Empirical sparse regression on quadratic manifolds. - Paul Schwerdtner; Serkan Gugercin; Benjamin Peherstorfer (CoRR, 2024)

Nonlinear Embeddings for Conserving Hamiltonians and Other Quantities with Neural Galerkin Schemes. - Paul Schwerdtner; Philipp Schulze; Jules Berman; Benjamin Peherstorfer (SIAM J. Sci. Comput., 2024)

Nonlinear model reduction with Neural Galerkin schemes on quadratic manifolds. - Philipp Weder; Paul Schwerdtner; Benjamin Peherstorfer (J. Comput. Phys., 2025)

Energy Matching in Reduced Passive and Port-Hamiltonian Systems. - Tobias Holicki; Jonas Nicodemus; Paul Schwerdtner; Benjamin Unger (SIAM J. Control. Optim., 2025)

Structured Optimization-Based Model Order Reduction for Parametric Systems. - Paul Schwerdtner; Manuel Schaller (SIAM J. Sci. Comput., 2025)

Operator Inference Aware Quadratic Manifolds with Isotropic Reduced Coordinates for Nonintrusive Model Reduction. - Paul Schwerdtner; Prakash Mohan 004; Julie Bessac; Marc T. Henry de Frahan; Benjamin Peherstorfer (CoRR, 2025)