Data Science / Representation Learning and Data Visualization

We develop machine learning tools for visualizing high-dimensional data such as single cell transcriptomics, clinical images, or scientific texts.

01
González-Márquez, R., Schmidt, L., Schmidt, B. M., Berens, P., & Kobak, D.

The landscape of biomedical research

Apr 09, 2024 | Patterns, 100968
02
Böhm, J. N., Berens, P., & Kobak, D.

Unsupervised visualization of image datasets using contrastive learning

May 30, 2023 | Proceedings of the International Conference on Learning Representations (ICLR)
03
Damrich, S., Böhm, J. N., Hamprecht, F. A., & Kobak, D.

From t-SNE to UMAP with contrastive learning

May 30, 2023 | Proceedings of the International Conference on Learning Representations (ICLR)
04
Böhm, J. N., Berens, P., & Kobak, D.

Attraction-repulsion spectrum in neighbor embeddings

Feb 21, 2022 | The Journal of Machine Learning Research, 23(1), 95, 4118–4149
05
Böhm, J. N., Berens, P., & Kobak, D.

Attraction-repulsion spectrum in neighbor embeddings

Jan 01, 2022 | The Journal of Machine Learning Research, 23(1), 4118-4149.
06
Scala, F., Kobak, D., Bernabucci, M., Bernaerts, Y., Cadwell, C. R., Castro, J. R., [...], Berens, P. & Tolias, A. S.

Phenotypic variation of transcriptomic cell types in mouse motor cortex

Oct 07, 2021 | Nature, 598(7879), 144-150
07
Ilanchezian, I., Kobak, D., Faber, H., Ziemssen, F., Berens, P., & Ayhan, M. S

Interpretable gender classification from retinal fundus images using BagNets.

Sep 21, 2021 | Proceedings, Part III 24 (pp. 477-487). Springer International Publishing.
08
Lause, J., Berens, P., & Kobak, D.

Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data.

Sep 09, 2021 | Genome biology, 22(1), 1-20
09
Kobak, D., Bernaerts, Y., Weis, M. A., Scala, F., Tolias, A. S., & Berens, P.

Sparse reduced-rank regression for exploratory visualisation of paired multivariate data

Aug 07, 2021 | Journal of the Royal Statistical Society Series C: Applied Statistics, 70(4), 980-1000
11
Kobak, D., & Linderman, G. C.

Initialization is critical for preserving global data structure in both t-SNE and UMAP

Feb 01, 2021 | Nature biotechnology, 39(2), 156-157.
12
Kobak, D., & Berens, P.

The art of using t-SNE for single-cell transcriptomics.

Nov 28, 2019 | Nature communications, 10(1), 5416.
13
Kobak, D., Linderman, G., Steinerberger, S., Kluger, Y., & Berens, P.

Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations.

Sep 16, 2019 | Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Cham: Springer International Publishing, 2019.