A Unifying Perspective on Neighbor Embeddings along the Attraction-Repulsion Spectrum. - Jan Niklas Böhm; Philipp Berens; Dmitry Kobak (CoRR, 2020)

Contrastive learning unifies t-SNE and UMAP. - Sebastian Damrich; Jan Niklas Böhm; Fred A. Hamprecht; Dmitry Kobak (CoRR, 2022)

Attraction-Repulsion Spectrum in Neighbor Embeddings. - Jan Niklas Böhm; Philipp Berens; Dmitry Kobak (J. Mach. Learn. Res., 2022)

Unsupervised visualization of image datasets using contrastive learning. - Jan Niklas Böhm; Philipp Berens; Dmitry Kobak (ICLR, 2023)

From $t$-SNE to UMAP with contrastive learning. - Sebastian Damrich; Jan Niklas Böhm; Fred A. Hamprecht; Dmitry Kobak (ICLR, 2023)

Self-supervised Visualisation of Medical Image Datasets. - Ifeoma Veronica Nwabufo; Jan Niklas Böhm; Philipp Berens; Dmitry Kobak (CoRR, 2024)

On the Importance of Embedding Norms in Self-Supervised Learning. - Andrew Draganov; Sharvaree P. Vadgama; Sebastian Damrich; Jan Niklas Böhm; Lucas Maes; Dmitry Kobak; Erik J. Bekkers (CoRR, 2025)

Node Embeddings via Neighbor Embeddings. - Jan Niklas Böhm; Marius Keute; Alica Guzmán; Sebastian Damrich; Andrew Draganov; Dmitry Kobak (CoRR, 2025)