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 • 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 • 16 Jan 2014 • Alexander Feldman, Gregory Provan, Arjan van Gemund
Model-based diagnostic reasoning often leads to a large number of diagnostic hypotheses.
no code implementations • 16 Jan 2014 • Alexander Feldman, Gregory Provan, Arjan van Gemund
We propose a StochAstic Fault diagnosis AlgoRIthm, called SAFARI, which trades off guarantees of computing minimal diagnoses for computational efficiency.