AI RESEARCH
ToMAToMP: Robust and Multi-Parameter Topological Clustering
arXiv CS.LG
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ArXi:2605.14824v1 Announce Type: new Topological clustering, and its main algorithm ToMATo, is a clustering method from Topological Data Analysis (TDA) which has been applied successfully in several applications during the last few years. This is due to its high versatility, as clusters are detected from the persistent components in the sublevel sets of any user-defined function (gene expression, pixel values, etc), and efficiency, as topological clustering enjoys robustness guarantees. However, ToMATo is also limited in several ways.