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Learning by Confusion Locates a Parametrization-Dependent Fisher Information Maximum
Learning by confusion (LBC) is a machine-learning method for locating phase transitions without assuming a known order parameter. Its characteristic accuracy curve contains a central maximum that is interpreted as the transition point, but what determines the location and finite-size scaling of this
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