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Many current approaches to machine learning in particle physics use generic architectures that require large numbers of parameters and disregard underlying physics principles, limiting their applicability as scientific modeling tools.
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Alexander Bogatskiy, Brandon Anderson, Jan. Offermann, Marwah Roussi, David. Miller and Risi Kondor · 2006
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