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Ball mapper: a shape summary for topological data analysis
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Topological data analysis provides a collection of tools to encapsulate and summarize the shape of data. Currently it is mainly restricted to \emph{mapper algorithm} and \emph{persistent homology}. In this paper we introduce new mapper--inspired descriptor that can be applied for exploratory data analysis.
Forward citations
Cited by 3 Pith papers
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Explainable Mapper: Charting LLM Embedding Spaces Using Perturbation-Based Explanation and Verification Agents
A visual analytics workspace uses LLM explanation and verification agents to semi-automatically annotate and perturbation-check mapper graph elements of BERT embeddings, replicating known layer-wise linguistic patterns.
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A Three Axis Evaluation Framework for Mapper Algorithms
The paper reviews a three-axis evaluation framework (stability, cluster quality, topological shape preservation) for Mapper algorithms, analyzes variants on synthetic and UCI Digits data, and finds the axes often conf...
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Exact and Approximate Range Queries for Efficient Ball Mapper Construction
Ball tree and FAISS range-query acceleration speeds up Ball Mapper cover construction by up to two orders of magnitude versus the reference implementation, at the cost of higher memory use.
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