Understanding the eye through data — from single synapses to population-scale disease.
01
Boreiko, V., Augustin, M., Croce, F., Berens, P., & Hein, M.
Sparse visual counterfactual explanations in image space
02
Müller, S., Koch, L. M., Lensch, H., & Berens, P.
A Generative Model Reveals the Influence of Patient Attributes on Fundus Images
03
Koch, L. M., Schürch, C. M., Gretton, A., & Berens, P.
Hidden in plain sight: Subgroup shifts escape ood detection
04
05
Beck, J., Deistler, M., Bernaerts, Y., Macke, J. H., & Berens, P
Efficient identification of informative features in simulation-based inference
06
Böhm, J. N., Berens, P., & Kobak, D.
Attraction-repulsion spectrum in neighbor embeddings
07
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
08
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
09
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
10
Oesterle, J., Krämer, N., Hennig, P., & Berens, P.
Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models
11
Faber, H., Berens, P., & Rohrbach, J. M.
Ocular changes as a diagnostic tool for malaria
12
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
13
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.
14
Gonschorek, D., Höfling, L., Szatko, K. P., Franke, K., Schubert, T., Dunn, B., Berens, P. ... & Euler, T.
Removing inter-experimental variability from functional data in systems neuroscience.
15
BRAIN Initiative Cell Census Network (BICCN)
A multimodal cell census and atlas of the mammalian primary motor cortex
16
Yoshimatsu, T., Bartel, P., Schröder, C., Janiak, F. K., St-Pierre, F., Berens, P., & Baden, T.