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This paper introduces a method for efficiently inferring a high-dimensional distributed quantity from a few observations. The quantity of interest (QoI) is approximated in a basis (dictionary) learned from a training set. The coefficients associated with the approximation of the QoI in the basis are determined by minimizing the misfit with the observations. To obtain a probabilistic estimate of the...
Sensor placement is of pivotal importance in closed-loop control as measurements are key to design the control laws. In this article, a novel machine learning-based sensor placement algorithm is proposed in order to recover a high-dimensional field from a limited amount of local measurements with a linear estimator. Unlike many other methods, our algorithm does not rely on a reduced order model and...
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