717 citations · 901 across the 13 of their papers we have counts for
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cs.LG2022★ 7 cited
Unsupervised visualization of image datasets using contrastive learning
Jan Niklas Böhm, Philipp Berens, Dmitry Kobak
Visualization methods based on the nearest neighbor graph, such as t-SNE or UMAP, are widely used for visualizing high-dimensional data. Yet, these approaches only produce meaningf…
cs.LG2022★ 4 cited
From -SNE to UMAP with contrastive learning
Sebastian Damrich, Jan Niklas Böhm, Fred A. Hamprecht +1
Neighbor embedding methods -SNE and UMAP are the de facto standard for visualizing high-dimensional datasets. Motivated from entirely different viewpoints, their loss functions…