Uncertainty quantification of limit-cycle oscillations. - Philip S. Beran; Chris L. Pettit; Daniel R. Millman (J. Comput. Phys., 2006)

Toward a definition and understanding of correlation for variables constrained by random relations. - Fulvio Tonon; Chris L. Pettit (Int. J. Gen. Syst., 2010)

Optimal sensor placement with signal propagation effects and inhomogeneous coverage preferences. - Sergey N. Vecherin; D. Keith Wilson; Chris L. Pettit (Int. J. Sens. Networks, 2011)

General software for multimodal signal modeling and optimal sensor placement: Environmental Awareness for Sensor and Emitter Employment (EASEE). - Kenneth K. Yamamoto; Sergey N. Vecherin; D. Keith Wilson; Christian T. Borden; Elizabeth Bettencourt; Chris L. Pettit (ICCST, 2012)

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)

Optimisation of numbers, types, and locations of wireless sensors with communication, finite supply, and multiple-sensor coverage constraints. - Sergey N. Vecherin; D. Keith Wilson; Chris L. Pettit (Int. J. Sens. Networks, 2017)

Scattered signal distributions, parametric uncertainties, and Bayesian sequential updating. - D. Keith Wilson; Carl R. Hart; Chris L. Pettit; Daniel J. Breton; Edward T. Nykaza; Vladimir E. Ostashev (Proc. Meet. Acoust., 2017)

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

Domain Decomposition of Stochastic PDEs: Development of Probabilistic Wirebasket-based Two-level Preconditioners. - Ajit Desai; Mohammad Khalil; Chris L. Pettit; Dominique Poirel; 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)

Probabilistic Prediction of Coalescence Flutter Using Measurements: Application to the Flutter Margin Method. - Sandip Chajjed; Mohammad Khalil; Dominique Poirel; Chris L. Pettit; 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)