Using topological autoencoders as a filtering function for global and local topology

NeurIPS Workshop TDA_and_Beyond 2020  ·  Filip Cornell ·

Choosing a suitable filtering function for the Mapper algorithm can be difficult due to its arbitrariness and domain-specific requirements. Finding a general filtering function that can be applied across domains is therefore of interest, since it would improve the representation of manifolds in higher dimensions. In this extended abstract, we propose that topological autoencoders is a suitable candidate for this and report initial results strengthening this hypothesis for one set of high-dimensional manifolds. The results indicate a potential for an easier choice of filtering function when using the Mapper algorithm, allowing for a more general and descriptive representation of high-dimensional data.

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