Publications of Peter Benner

Benner, P.; Grivet-Talocia, S.; Quarteroni, A.; Rozza, G.; Schilders, W.; Silveira, L. M.: Preface to the third Volume of Model Order Reduction. Model Order Reduction: Volume 3: Applications, pp. V - VI (2021)

Benner, P.; Grivet-Talocia, S.; Quarteroni, A.; Rozza, G.; Schilders, W.; Silveira, L. M.: Preface to the second Volume of Model Order Reduction. Model Order Reduction: Volume 2: Snapshot-Based Methods and Algorithms, pp. V - VI (2021)

Benner, P.; Grivet-Talocia, S.; Quarteroni, A.; Rozza, G.; Schilders, W.; Silveira, L. M.: Preface to the first Volume of Model Order Reduction. Model Order Reduction: Volume 1: System- and Data-Driven Methods and Algorithms, pp. V - VIII (2021)

Benner, P.; Quintana-Ortì, E.; Saak, J.: Introduction to the Special Issue related to the Power Aware Computing Workshop 2019 — PACO 2019. International Journal of High Performance Computing Applications 35 (3), pp. 209 - 210 (2021)

Benner, P.; Khoromskij, B. N.; Khoromskaia, V.; Sun, B.: A Mesh-Free Hybrid Chebyshev-Tucker Tensor Format with Applications to Multi-Particle Modelling. (2025)

Gkimisis, L.; Pontes Duff, I.; Goyal, P. K.; Benner, P.: On the Representation of Energy-Preserving Quadratic Operators with Application to Operator Inference. (2025)

Gkimisis, L.; Yildiz, S.; Benner, P.; Richter, T.: A CFL-type Condition and Theoretical Insights for Discrete-Time Sparse Full-Order Model Inference. (2025)

Kapadia, H.; Benner, P.; Feng, L.: Subspace-Distance-Enabled Active Learning for Efficient Data-Driven Model Reduction of Parametric Dynamical Systems. (2025)

Manvelyan-Stroot, D.; Filanova, Y.; Pontes Duff, I.; Benner, P.; Wever, U.: Inference of Substructured Reduced-Order Models for Dynamic Contact from Contact-free Simulations. (2025)

Monem Abdelhafez, S.; Benner, P.; Lessig, C.: SIGGRAPH: G: Improved Projective Dynamics Global Using Snapshots-based Reduced Bases. (2025)

Przybilla, J.; Ugrica Vukojević, M.; Truhar, N.; Benner, P.: An Adaptive Scheme for the Optimization of Damping Positions by Decoupling Controllability Spaces in Vibrational Systems. (2025)

Sun, S.; Feng, L.; Benner, P.: Interpretable Spatial-Temporal Fusion Transformers: Multi-Output Prediction for Parametric Dynamical Systems with Time-Varying Inputs. (2025)

Baran, B.; Benner, P.; Saak, J.; Stillfjord, T.: Numerical Methods for Closed-Loop Systems with Non-Autonomous Data. (2024)

Chellappa, S.; Feng, L.; Benner, P.: Discrete Empirical Interpolation in the Tensor t-Product Framework. (2024)

Chellappa, S.; Feng, L.; Benner, P.: Discrete Empirical Interpolation in the Tensor t-Product Framework. (2024)

Forootani, A.; Benner, P.: GN-SINDy: Greedy Sampling Neural Network in Sparse Identification of Nonlinear Partial Differential Equations. (2024)

Forootani, A.; Kapadia, H.; Chellappa, S.; Goyal, P. K.; Benner, P.: GS-PINN: Greedy Sampling for Parameter Estimation in Partial Differential Equations. (2024)

Khorrami, M. S.; Goyal, P. K.; Mianroodi, J. R.; Svendsen, B.; Benner, P.; Raabe, D.: Divergence-free Neural Operators for Stress Field Modeling in Polycrystalline Materials. (2024)

Mlinarić, P.; Benner, P.; Gugercin, S.: Interpolatory Necessary Optimality Conditions for Reduced-order Modeling of Parametric Linear Time-invariant Systems. (2024)

Naumann, C.; Kumar, T. S.; Vettermann, J.; Geist, A.; Saak, J.; Benner, P.; Ihlenfeldt, S.: Training of Artificial Neural Networks with Reduced-Order Models for the Prediction of Thermal Errors on Machine Tools. Research Square (2024)