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Robust Topological Inference: Distance To a Measure and Kernel Distance

22 Dec 2014 • Frédéric Chazal • Brittany T. Fasy • Fabrizio Lecci • Bertrand Michel • Alessandro Rinaldo • Larry Wasserman

Let P be a distribution with support S. The salient features of S can be quantified with persistent homology, which summarizes topological features of the sublevel sets of the distance function (the distance of any point x to S). Given a sample from P we can infer the persistent homology using an empirical version of the distance function... (read more)

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MathieuCarriere/sklearn_tda

MathieuCarriere/sklearn-tda

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Robust Topological Inference: Distance To a Measure and Kernel Distance

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