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Graph Neural Networks for Maximum Constraint Satisfaction

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Many combinatorial optimization problems can be phrased in the language of constraint satisfaction problems. We introduce a graph neural network architecture for solving such optimization problems. The architecture is generic; it works for all binary constraint satisfaction problems. https://www.markymarkscott.com/product-category/peanut/
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