Machine Learning Approaches for Inverse Problems and Optimal Design in Electromagnetism
Alessandro Formisano,
Mauro Tucci
Abstract:The spread of high-performance personal computers, frequently equipped with powerful Graphic Processing Units (GPUs), has raised interest in a set of techniques that are able to extract models of electromagnetic phenomena (and devices) directly from available examples of desired behavior. Such approaches are collectively referred to as Machine Learning (ML). A typical representative ML approach is the so-called “Neural Network” (NN). Using such data-driven models allows the evaluation of the output in a much s… Show more
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