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Interpretable machine learning in Physics
Published 11 Mar 2022 in hep-ph and cs.LG | (2203.08021v3)
Abstract: Adding interpretability to multivariate methods creates a powerful synergy for exploring complex physical systems with higher order correlations while bringing about a degree of clarity in the underlying dynamics of the system.
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