Publications of Pawan Kumar Goyal

Goyal, P. K.; Benner, P.: Model order reduction of stokes-type bilinear descriptor systems. Recent trends and future developments in Computational Science & Engineering, Plön, Germany (2015)

Goyal, P. K.; Heiland, J.; Ahmad, M. I.; Benner, P.: Interpolary Model Reduction for Stokes-type Quadratic-Bilinear Systems. International Conference on Scientific Computation And Differential Equations 2015 (SciCADE 2015), Potsdam, Germany (2015)

Goyal, P. K.: Interpolatory Model Order Reduction for Bilinear Descriptor Systems. Reduced Basis Summer School 2014, Münster, Germany (2014)

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)

Goyal, P. K.: Interpolatory model reduction for bilinear descriptor systems. Workshop on Model Reduction, Pilsen, Czech Republic (2015)

Goyal, P. K.: System-Theoretic Model Order Reduction for Bilinear and Quadratic-Bilinear Control Systems. Dissertation, Otto-von-Guericke-Universität, Magdeburg (2018)

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

Reddig, C.; Goyal, P. K.; Pontes Duff, I.; Benner, P.: Active Sampling of Interpolation Points to Identify Dominant Subspaces for Model Reduction. (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)

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

Przybilla, J.; Pontes Duff, I.; Goyal, P. K.; Benner, P.: Balanced Truncation of Descriptor Systems with a Quadratic Output. (2024)

Goyal, P. K.; Pontes Duff, I.; Benner, P.: Guaranteed Stable Quadratic Models and their applications in SINDy and Operator Inference. (2023)

Yildiz, S.; Goyal, P. K.; Benner, P.: Linearly Implicit Global Energy Preserving Reduced-order Models for Cubic Hamiltonian Systems. (2023)

Goyal, P. K.; Pontes Duff, I.; Benner, P.: Inference of Continuous Linear Systems from Data with Guaranteed Stability. (2023)

Goyal, P. K.; Benner, P.: Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning. (2021)

Goyal, P. K.; Benner, P.: LQResNet: A Deep Neural Network Architecture for Learning Dynamic Processes. (2021)

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)

Goyal, P. K.; Daas, H. A.; Benner, P.: Low-Rank and Total Variation Regularization and Its Application to Image Recovery. (2020)