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Mixed Integer Neural Inverse Design
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DescriptionNeural networks are among the most common modeling surrogates, and their inversion is crucial to finding designs with desirable performances. We have reformulated and solved the neural inverse design problem as a mixed integer linear programming, which is capable of finding globally optimum designs and handling combinatorial design constraints.