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In this article, we study Euler characteristic techniques in topological data analysis.
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A survey of topological machine learning methods
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On approximation theorems for the euler characteristic with applications to the bootstrap
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Limit theorems for persistence diagrams
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Generic two-parameter persistence modules are nearly indecomposable
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Randomness of shapes and statistical inference on shapes via the smooth euler characteristic transform
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