no code implementations • 8 Jun 2023 • Ion Matei, Raj Minhas, Johan de Kleer, Alexander Felman
In this paper, we explore how AI tools can be useful in control applications.
no code implementations • 8 Sep 2022 • Alexander Feldman, Johan de Kleer, Ion Matei
In this paper we provide a novel approach for computing diagnosis of switching circuits with gate-based quantum computers.
no code implementations • 30 Aug 2022 • Ion Matei, Wiktor Piotrowski, Alexandre Perez, Johan de Kleer, Jorge Tierno, Wendy Mungovan, Vance Turnewitsch
The framework is based on a physics-based digital twin model and three modules tasked with real-time fault diagnosis, prognostics and reconfiguration.
no code implementations • 26 Aug 2022 • Ion Matei, Maksym Zhenirovskyy, Johan de Kleer, John Maxwell
In our second algorithm, we use an ODE solver to reset the ODE solution, but no direct are adjoint sensitivity analysis methods are used.
no code implementations • 22 Mar 2020 • Ion Matei, Johan de Kleer, Christoforos Somarakis, Rahul Rai, John S. Baras
We describe how we can build models out of the p-H constructs and how we can train them.
no code implementations • 4 Mar 2020 • Ion Matei, Johan de Kleer, Alexander Feldman, Rahul Rai, Souma Chowdhury
In this paper, we outline a novel hybrid modeling approach that combines machine learning inspired models and physics-based models to generate reduced-order models from high fidelity models.
no code implementations • 7 May 2019 • Alexander Feldman, Johan de Kleer, Ion Matei
We apply our method to the design of Boolean systems and discover new and more optimal classical digital and quantum circuits for common arithmetic functions such as addition and multiplication.
no code implementations • 14 Jul 2017 • Jonathan Rubin, Rui Abreu, Anurag Ganguli, Saigopal Nelaturi, Ion Matei, Kumar Sricharan
The work presented here applies deep learning to the task of automated cardiac auscultation, i. e. recognizing abnormalities in heart sounds.