Berens, Philipp

20 publications

NeurIPS 2025 A Data and Task-Constrained Mechanistic Model of the Mouse Outer Retina Shows Robustness to Contrast Variations Kyra L. Kadhim, Jonas Beck, Ziwei Huang, Jakob H. Macke, Fred Rieke, Thomas Euler, Michael Deistler, Philipp Berens

NeurIPS 2025 TRACE: Contrastive Learning for Multi-Trial Time Series Data in Neuroscience Lisa Schmors, Dominic Gonschorek, Jan Niklas Böhm, Yongrong Qiu, Na Zhou, Dmitry Kobak, Andreas S. Tolias, Fabian H. Sinz, Jacob Reimer, Katrin Franke, Sebastian Damrich, Philipp Berens

ICML 2024 Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations Jonas Beck, Nathanael Bosch, Michael Deistler, Kyra L. Kadhim, Jakob H. Macke, Philipp Hennig, Philipp Berens

MIDL 2024 Efficiently Correcting Patch-Based Segmentation Errors to Control Image-Level Performance in Retinal Images Patrick Köhler, Jeremiah Fadugba, Philipp Berens, Lisa M. Koch

MIDL 2024 Leveraging Probabilistic Segmentation Models for Improved Glaucoma Diagnosis: A Clinical Pipeline Approach Anna M. Wundram, Paul Fischer, Stephan Wunderlich, Hanna Faber, Lisa M. Koch, Philipp Berens, Christian F. Baumgartner

ICLR 2024 Most Discriminative Stimuli for Functional Cell Type Clustering Max F Burg, Thomas Zenkel, Michaela Vystrčilová, Jonathan Oesterle, Larissa Höfling, Konstantin Friedrich Willeke, Jan Lause, Sarah Müller, Paul G. Fahey, Zhiwei Ding, Kelli Restivo, Shashwat Sridhar, Tim Gollisch, Philipp Berens, Andreas S. Tolias, Thomas Euler, Matthias Bethge, Alexander S Ecker

NeurIPS 2024 Persistent Homology for High-Dimensional Data Based on Spectral Methods Sebastian Damrich, Philipp Berens, Dmitry Kobak

MIDL 2023 Hidden in Plain Sight: Subgroup Shifts Escape OOD Detection Lisa M Koch, Christian M Schürch, Arthur Gretton, Philipp Berens

ICLR 2023 Unsupervised Visualization of Image Datasets Using Contrastive Learning Niklas Böhm, Philipp Berens, Dmitry Kobak

JMLR 2022 Attraction-Repulsion Spectrum in Neighbor Embeddings Jan Niklas Böhm, Philipp Berens, Dmitry Kobak

NeurIPS 2022 Efficient Identification of Informative Features in Simulation-Based Inference Jonas Beck, Michael Deistler, Yves Bernaerts, Jakob H Macke, Philipp Berens

ICLRW 2022 Two-Dimensional Visualization of Large Document Libraries Using T-SNE Rita González-Márquez, Philipp Berens, Dmitry Kobak

ICML 2021 MorphVAE: Generating Neural Morphologies from 3D-Walks Using a Variational Autoencoder with Spherical Latent Space Sophie C. Laturnus, Philipp Berens

NeurIPS 2021 Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience Dominic Gonschorek, Larissa Höfling, Klaudia P. Szatko, Katrin Franke, Timm Schubert, Benjamin Dunn, Philipp Berens, David Klindt, Thomas Euler

NeurIPS 2020 System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina Cornelius Schröder, David Klindt, Sarah Strauss, Katrin Franke, Matthias Bethge, Thomas Euler, Philipp Berens

NeurIPS 2019 Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse Cornelius Schröder, Ben James, Leon Lagnado, Philipp Berens

ECML-PKDD 2019 Heavy-Tailed Kernels Reveal a Finer Cluster Structure in T-SNE Visualisations Dmitry Kobak, George C. Linderman, Stefan Steinerberger, Yuval Kluger, Philipp Berens

NeurIPS 2009 A Joint Maximum-Entropy Model for Binary Neural Population Patterns and Continuous Signals Sebastian Gerwinn, Philipp Berens, Matthias Bethge

NeurIPS 2009 Neurometric Function Analysis of Population Codes Philipp Berens, Sebastian Gerwinn, Alexander Ecker, Matthias Bethge

NeurIPS 2007 Near-Maximum Entropy Models for Binary Neural Representations of Natural Images Matthias Bethge, Philipp Berens