Bayesian inference of nonlinear unsteady aerodynamics from aeroelastic limit cycle oscillations. - Rimple Sandhu; Dominique Poirel; Chris L. Pettit; Mohammad Khalil; Abhijit Sarkar (J. Comput. Phys., 2016)

Nonlinear sparse Bayesian learning for physics-based models. - Rimple Sandhu; Mohammad Khalil; Chris L. Pettit; Dominique Poirel; Abhijit Sarkar (J. Comput. Phys., 2021)

Encoding nonlinear and unsteady aerodynamics of limit cycle oscillations using nonlinear sparse Bayesian learning. - Rimple Sandhu; Brandon Robinson; Mohammad Khalil; Chris L. Pettit; Dominique Poirel; Abhijit Sarkar (CoRR, 2022)

Exploring hierarchical framework of nonlinear sparse Bayesian learning algorithm through numerical investigations. - Nastaran Dabiran; Brandon Robinson; Rimple Sandhu; Mohammad Khalil; Chris L. Pettit; Dominique Poirel; Abhijit Sarkar (CoRR, 2023)

Sparse Bayesian neural networks for regression: Tackling overfitting and computational challenges in uncertainty quantification. - Nastaran Dabiran; Brandon Robinson; Rimple Sandhu; Mohammad Khalil; Dominique Poirel; Abhijit Sarkar (CoRR, 2023)

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System. - Faizan Mir; Stanley Young; Rimple Sandhu; Qichao Wang (ITSC, 2024)