3 papers
cs.LG2026
Persistent Multiscale Density-based Clustering
Daniël Bot, Leland McInnes, Jan Aerts
Clustering is a cornerstone of modern data analysis. Detecting clusters in exploratory data analyses (EDA) requires algorithms that make few assumptions about the data. Density-bas…
cs.LG2025
Low-dimensional embeddings of high-dimensional data
Cyril de Bodt, Alex Diaz-Papkovich, Michael Bleher +18
Large collections of high-dimensional data have become nearly ubiquitous across many academic fields and application domains, ranging from biology to the humanities. Since working…
cs.LG2025
Improving Mapper's Robustness by Varying Resolution According to Lens-Space Density
Kaleb D. Ruscitti, Leland McInnes
We propose a modification of the Mapper algorithm that removes the assumption of a single resolution scale across semantic space and improves the robustness of the results under ch…