Publications of Pawan Kumar Goyal

Benner, P.; Goyal, P. K.; Heiland, J.; Pontes Duff, I.: A Quadratic Decoder Approach to Nonintrusive Reduced-Order Modeling of Nonlinear Dynamical Systems. 92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics, Aachen, Germany, August 15, 2022 - August 19, 2022. Proceedings in Applied Mathematics and Mechanics 23 (1), e202200049, (2023)

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

Forootani, A.; Goyal, P. K.; Benner, P.: A Robust SINDy Approach by Combining Neural Networks and an Integral Form. (2023)

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

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

Goyal, P. K.; Yildiz, S.; Benner, P.: Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics. (2023)

Yildiz, S.; Goyal, P. K.; Bendokat, T.; Benner, P.: Data-Driven Identification of Quadratic Symplectic Representations of Nonlinear Hamiltonian Systems. (2023)

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

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. (2021)

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

Benner, P.; Goyal, P. K.: Balanced Truncation Model Order Reduction For Quadratic-Bilinear Control Systems. (2017)