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We explore the potential of Graph Neural Networks (GNNs) to improve the performance of high-dimensional effective field theory parameter fits to collider data beyond traditional rectangular cut-based differential distribution analyses.
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I. Brivio, SMEFTsim 3.0 — a practical guide , JHEP 04
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