Publications of Peter Benner

Poster (6)

2016
Poster
Bremer, J.; Goyal, P. K.; Feng, L.; Benner, P.; Sundmacher, K.: Optimization and Reduced Order Modeling of CO2 Methanation Reactors. KoMSO Challenge Workshop "Reduced-Order Modeling for Simulation and Optimization"​, Renningen, Germany (2016)
2015
Poster
Bremer, J.; Feng, L.; Benner, P.; Sundmacher, K.: Quadratic Approximation for Model Order Reduction in Reaction Engineering. MORE - Workshop on MOdel REduction, Pilsen, Czech Republic (2015)

Thesis - PhD (1)

1997
Thesis - PhD
Benner, P.: Contributions to the Numerical Solution of Algebraic Riccati Equations and Related Eigenvalue Problems. Dissertation, 228 pp., Logos-Verlag, Berlin (1997)

Thesis - Master (1)

1993
Thesis - Master
Benner, P.: Ein orthogonal symplektischer Multishift Algorithms zur Lösung der algebraischen Riccatigleichung. Master (1993)

Working Paper (29)

2022
Working Paper
Benner, P.; Faßbender, H.; Senn, M.-N.: The Hamiltonian Extended Krylov Subspace Method. (2022)
Working Paper
Benner, P.; Gugercin, S.; Werner, S. W. R.: A Unifying Framework for Tangential Interpolation of Structured Bilinear Control Systems. (2022)
Working Paper
Benner, P.; Nakatsukasa, Y.; Penke, C.: A Structure-Preserving Divide-and-Conquer Method for Pseudosymmetric Matrices. (2022)
Working Paper
Benner, P.; Palitta, D.; Saak, J.: Krylov Techniques for Low-Rank ADI. (2022)
Working Paper
Goyal, P. K.; Benner, P.: Neural ODEs with Irregular and Noisy Data. (2022)
Working Paper
Przybilla, J.; Pontes Duff, I.; Benner, P.: Model Reduction for Second-Order Systems with Inhomogeneous Initial Conditions. (2022)
2021
Working Paper
Chellappa, S.; Feng, L.; de la Rubia, V.; Benner, P.: Inf-Sup-Constant-Free State Error Estimator for Model Order Reduction of Parametric Systems in Electromagnetics. (2021)
Working Paper
Goyal, P. K.; Benner, P.: LQResNet: A Deep Neural Network Architecture for Learning Dynamic Processes. (2021)
Working Paper
Goyal, P. K.; Benner, P.: Learning Dynamics from Noisy Measurements using Deep Learning with a Runge-Kutta Constraint. The Symbiosis of Deep Learning and Differential Equations Workshop at NeurIPS 2021, 9 pages (2021)
Working Paper
Goyal, P. K.; Benner, P.: Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning. (2021)
Working Paper
Himpe, C.; Grundel, S.; Benner, P.: Next-Gen Gas Network Simulation. (2021)
Working Paper
Khattak, M. A.; Ahmad, M. I.; Feng, L.; Benner, P.: Multivariate Moment Matching for Model Order Reduction of Quadratic-Bilinear Systems using Error Bounds. (2021)
Working Paper
Kweyu, C. M.; Khoromskaia, V.; Khoromskij, B.; Stein, M.; Benner, P.: Solution Decomposition for the Nonlinear Poisson-Boltzmann Equation using the Range-Separated Tensor Format. (2021)
Working Paper
Sarna, N.; Benner, P.: Learning Reduced Order Models from Data for Hyperbolic PDEs. (2021)
2020
Working Paper
Banagaaya, N.; Ali, G.; Grundel, S.; Benner, P.: Automatic Decoupling and Index-aware Model-Order Reduction for Nonlinear Differential-Algebraic Equations. (2020)
Working Paper
Beddig, R. S.; Benner, P.; Dorschky, I.; Reis, T.; Schwerdtner, P.; Voigt, M.; Werner, S. W. R.: Structure-Preserving Model Reduction for Dissipative Mechanical Systems. (2020)
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