Publications of Pawan Kumar Goyal

Goyal, P. K. & Benner, P.Model order reduction of stokes-type bilinear descriptor systemsPresented at: Recent trends and future developments in Computational Science & EngineeringPlön, Germany, March 9, 2015.

Goyal, P. K., Heiland, J., Ahmad, M. I., & Benner, P.Interpolary Model Reduction for Stokes-type Quadratic-Bilinear SystemsPresented at: International Conference on Scientific Computation And Differential Equations 2015 (SciCADE 2015)Potsdam, Germany, September 14, 2015.

Goyal, P. K.Interpolatory Model Order Reduction for Bilinear Descriptor SystemsPresented at: Reduced Basis Summer School 2014Münster, Germany, August 18, 2014.

Bremer, J., Goyal, P. K., Feng, L., Benner, P., & Sundmacher, K.Optimization and Reduced Order Modeling of CO₂ Methanation ReactorsPresented at: KoMSO Challenge Workshop "Reduced-Order Modeling for Simulation and Optimization"​Renningen, Germany, November 17, 2016.

Goyal, P. K.Interpolatory model reduction for bilinear descriptor systemsPresented at: Workshop on Model ReductionPilsen, Czech Republic, September 6, 2015.

Goyal, P. K. (2018)System-Theoretic Model Order Reduction for Bilinear and Quadratic-Bilinear Control SystemsPhD Thesis, Otto-von-Guericke-Universität, Magdeburgdoi: 10.25673/5319.

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

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

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

Przybilla, J., Pontes Duff, I., Goyal, P. K., & Benner, P. (in press)Balanced Truncation of Descriptor Systems with a Quadratic Output.

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

Goyal, P. K., Pontes Duff, I., & Benner, P. (in press)Inference of Continuous Linear Systems from Data with Guaranteed Stability.

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

Yildiz, S., Goyal, P. K., & Benner, P. (in press)Linearly Implicit Global Energy Preserving Reduced-order Models for Cubic Hamiltonian Systems.

Goyal, P. K. & Benner, P. (in press)LQResNet: A Deep Neural Network Architecture for Learning Dynamic Processes.

Goyal, P. K. & Benner, P. (2021)Learning Dynamics from Noisy Measurements using Deep Learning with a Runge-Kutta ConstraintThe Symbiosis of Deep Learning and Differential Equations Workshop at NeurIPS 2021, 9 pages.

Goyal, P. K. & Benner, P. (in press)Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning.

Goyal, P. K., Daas, H. A., & Benner, P. (in press)Low-Rank and Total Variation Regularization and Its Application to Image Recovery.