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Deep Learning with Topological Signatures

NeurIPS 2017 • Christoph Hofer • Roland Kwitt • Marc Niethammer • Andreas Uhl

Inferring topological and geometrical information from data can offer an alternative perspective on machine learning problems. Methods from topological data analysis, e.g., persistent homology, enable us to obtain such information, typically in the form of summary representations of topological features... (read more)

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c-hofer/nips2017 official

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c-hofer/persistent_homology_toolbox official

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billy-mosse/spiderman

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ssmele/CompTopoProg

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TOPOLOGICAL DATA ANALYSIS

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