Scalable Computational Algorithms for Geo-spatial Covid-19 Spread in High Performance Computing. - Sudhi P. V.; Victorita Dolean; Pierre Jolivet; Brandon Robinson; Jodi D. Edwards; Tetyana Kendzerska; Abhijit Sarkar (CoRR, 2022)

Robust Bayesian state and parameter estimation framework for stochastic dynamical systems with combined time-varying and time-invariant parameters. - Philippe Bisaillon; Brandon Robinson; Mohammad Khalil; Chris L. Pettit; Dominique Poirel; Abhijit Sarkar (CoRR, 2022)

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)

A Bayesian model calibration framework for stochastic compartmental models with both time-varying and time-invariant parameters. - Brandon Robinson; Philippe Bisaillon; Jodi D. Edwards; Tetyana Kendzerska; Mohammad Khalil; Dominique Poirel; Abhijit Sarkar (CoRR, 2023)