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cs.LG2023
Persistent Homology for High-dimensional Data Based on Spectral Methods
Sebastian Damrich, Philipp Berens, Dmitry Kobak
Persistent homology is a popular computational tool for analyzing the topology of point clouds, such as the presence of loops or voids. However, many real-world datasets with low i…
cs.LG2019
Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations
Dmitry Kobak, George Linderman, Stefan Steinerberger +2
T-distributed stochastic neighbour embedding (t-SNE) is a widely used data visualisation technique. It differs from its predecessor SNE by the low-dimensional similarity kernel: th…