In the Department of Data Science we generate knowledge from data to advance neuroscience and ophthalmology.
01
Bachmann, F., Hennig, P., Kobak, D.
Wasserstein tSNE
02
Janschewski, J., Käppler, C., & Berens, P.
School predictors of mental health problems in children and adolescents based on a survey of students in hospital and regular schools
03
Boreiko, V., Augustin, M., Croce, F., Berens, P., & Hein, M.
Sparse visual counterfactual explanations in image space
04
Müller, S., Koch, L. M., Lensch, H., & Berens, P.
A Generative Model Reveals the Influence of Patient Attributes on Fundus Images
05
Koch, L. M., Schürch, C. M., Gretton, A., & Berens, P.
Hidden in plain sight: Subgroup shifts escape ood detection
06
07
Beck, J., Deistler, M., Bernaerts, Y., Macke, J. H., & Berens, P
Efficient identification of informative features in simulation-based inference
08
Böhm, J. N., Berens, P., & Kobak, D.
Attraction-repulsion spectrum in neighbor embeddings
09
Blum, C., Baur, D., Achauer, L. C., Berens, P., [...], Huang, Z., [...] , Macke, J.H., [...] & Ziemann, U.
Personalized neurorehabilitative precision medicine: from data to therapies (MWKNeuroReha)–a multi-centre prospective observational clinical trial to predict long-term outcome of patients with acute motor stroke
10
Strauss, S., Korympidou, M. M., Ran, Y., Franke, K., Schubert, T., Baden, T., Berens, P., Euler, T. & Vlasits, A. L
Center-surround interactions underlie bipolar cell motion sensitivity in the mouse retina
11
Boreiko, V., Ilanchezian, I., Ayhan, M. S., Müller, S., Koch, L. M., Faber, H., Berens, P. & Hein, M.
Visual explanations for the detection of diabetic retinopathy from retinal fundus images
12
Oesterle, J., Krämer, N., Hennig, P., & Berens, P.
Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models
13
Faber, H., Berens, P., & Rohrbach, J. M.
Ocular changes as a diagnostic tool for malaria
14
Ayhan, M. S., Kümmerle, L. B., Kühlewein, L., Inhoffen, W., Aliyeva, G., Ziemssen, F., & Berens, P.
Clinical validation of saliency maps for understanding deep neural networks in ophthalmology
15
Behrens, C., Yadav, S. C., Korympidou, M. M., Zhang, Y., Haverkamp, S., Irsen, S., ... & Schubert, T.
Retinal horizontal cells use different synaptic sites for global feedforward and local feedback signaling.
16
Gonschorek, D., Höfling, L., Szatko, K. P., Franke, K., Schubert, T., Dunn, B., Berens, P. ... & Euler, T.