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cs.LG2023
Navigating Perplexity: A linear relationship with the data set size in t-SNE embeddings
Martin Skrodzki, Nicolas F. Chaves-de-Plaza, Thomas Höllt +2
Widely used pipelines for analyzing high-dimensional data utilize two-dimensional visualizations. These are created, for instance, via t-distributed stochastic neighbor embedding (…
cs.LG2023
Parametrizing Product Shape Manifolds by Composite Networks
Josua Sassen, Klaus Hildebrandt, Martin Rumpf +1
Parametrizations of data manifolds in shape spaces can be computed using the rich toolbox of Riemannian geometry. This, however, often comes with high computational costs, which ra…