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<p>Optimal sensor placement is an important problem
to look at. This problem becomes all the more relevant nowadays
due to advancements in infrastructure monitoring robotic technologies including underground sensing. While there are multiple
ways to solve optimal sensor placement problems, one of the
most generic methods available is Bayesian Optimization and
its variants. In this paper, we present a simple benchmark-
like formulation for exploiting Gaussian Process uncertainty for
sensor placement to measure a scalar field. </p>
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