Philipp Berens

82 papers A* 9Journal 55Unranked 18
YearRankTypeTitle / Venue / Authors
2026 J jnl
Cropping outperforms dropout as an augmentation strategy for self-supervised training of text embeddings.
Trans. Mach. Learn. Res.
Rita González-Márquez, Philipp Berens, Dmitry Kobak
2026 J jnl
Mitigating Shortcut Learning via Feature Disentanglement in Medical Imaging: A Benchmark Study.
CoRR
Sarah Müller, Philipp Berens
2026 J jnl
Ordinal Diffusion Models for Color Fundus Images.
CoRR
Gustav Schmidt, Philipp Berens, Sarah Müller
2026 J jnl
TTE-CAM: Built-in Class Activation Maps for Test-Time Explainability in Pretrained Black-Box CNNs.
CoRR
Kerol Djoumessi, Philipp Berens
2026 J jnl
Towards Interpretable Foundation Models for Retinal Fundus Images.
CoRR
Samuel Ofosu Mensah, Maria Camila Roa Carvajal, Kerol Djoumessi, Philipp Berens
2025 — conf
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Disease Detection from Retinal Fundus Images.
iMIMIC@MICCAI
Kerol Djoumessi, Samuel Ofosu Mensah, Philipp Berens
2025 J jnl
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Medical Image Classification.
CoRR
Kerol Djoumessi, Samuel Ofosu Mensah, Philipp Berens
2025 J jnl
Combined statistical-biophysical modeling links ion channel genes to physiology of cortical neuron types.
Patterns
Yves Bernaerts, Michael Deistler, Pedro J. Gonçalves, Jonas Beck, Marcel Stimberg, Federico Scala, Andreas S. Tolias, Jakob H. Macke, Dmitry Kobak, Philipp Berens
2025 J jnl
Cropping outperforms dropout as an augmentation strategy for training self-supervised text embeddings.
CoRR
Rita González-Márquez, Philipp Berens, Dmitry Kobak
2025 J jnl
Disentangling representations of retinal images with generative models.
Medical Image Anal.
Sarah Müller, Lisa M. Koch, Hendrik P. A. Lensch, Philipp Berens
2025 J jnl
Fundus Image Toolbox: A Python package for fundus image processing.
J. Open Source Softw.
Julius Gervelmeyer, Sarah Müller, Ziwei Huang, Philipp Berens
2025 — conf
Learning Disease State from Noisy Ordinal Disease Progression Labels.
MICCAI (5)
Gustav Schmidt, Holger Heidrich, Philipp Berens, Sarah Müller
2025 J jnl
Learning Disease State from Noisy Ordinal Disease Progression Labels.
CoRR
Gustav Schmidt, Holger Heidrich, Philipp Berens, Sarah Müller
2025 — conf
Prototype-Guided and Lightweight Adapters for Inherent Interpretation and Generalisation in Federated Learning.
MICCAI (7)
Samuel Ofosu Mensah, Kerol Djoumessi, Philipp Berens
2025 J jnl
Prototype-Guided and Lightweight Adapters for Inherent Interpretation and Generalisation in Federated Learning.
CoRR
Samuel Ofosu Mensah, Kerol Djoumessi, Philipp Berens
2025 J jnl
Soft-CAM: Making black box models self-explainable for high-stakes decisions.
CoRR
Kerol Djoumessi, Philipp Berens
2025 J jnl
Uncertainty-Aware Retinal Vessel Segmentation via Ensemble Distillation.
CoRR
Jeremiah Fadugba, Petru Manescu, Bolanle Oladejo, Delmiro Fernandez-Reyes, Philipp Berens
2024 J jnl
A computational approach to visual ecology with deep reinforcement learning.
CoRR
Sacha Sokoloski, Jure Majnik, Philipp Berens
2024 — conf
Benchmarking Dependence Measures to Prevent Shortcut Learning in Medical Imaging.
MLMI@MICCAI (2)
Sarah Müller, Louisa Fay, Lisa M. Koch, Sergios Gatidis, Thomas Küstner, Philipp Berens
2024 J jnl
Benchmarking Dependence Measures to Prevent Shortcut Learning in Medical Imaging.
CoRR
Sarah Müller, Louisa Fay, Lisa M. Koch, Sergios Gatidis, Thomas Küstner, Philipp Berens
2024 J jnl
Benchmarking Retinal Blood Vessel Segmentation Models for Cross-Dataset and Cross-Disease Generalization.
CoRR
Jeremiah Fadugba, Patrick Köhler, Lisa M. Koch, Petru Manescu, Philipp Berens
2024 A* conf
Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations.
ICML
Jonas Beck, Nathanael Bosch, Michael Deistler, Kyra L. Kadhim, Jakob H. Macke, Philipp Hennig, Philipp Berens
2024 J jnl
Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations.
CoRR
Jonas Beck, Nathanael Bosch, Michael Deistler, Kyra L. Kadhim, Jakob H. Macke, Philipp Hennig, Philipp Berens
2024 J jnl
Disentangling representations of retinal images with generative models.
CoRR
Sarah Müller, Lisa M. Koch, Hendrik P. A. Lensch, Philipp Berens
2024 J jnl
Distribution shift detection for the postmarket surveillance of medical AI algorithms: a retrospective simulation study.
npj Digit. Medicine
Lisa M. Koch, Christian F. Baumgartner, Philipp Berens
2024 — conf
Efficiently correcting patch-based segmentation errors to control image-level performance in retinal images.
MIDL
Patrick Köhler, Jeremiah Fadugba, Philipp Berens, Lisa M. Koch
2024 J jnl
Estimating Causal Effects with Double Machine Learning - A Method Evaluation.
CoRR
Jonathan Fuhr, Philipp Berens, Dominik Papies
2024 J jnl
Foundation models in healthcare require rethinking reliability.
Nat. Mac. Intell.
Thomas Grote, Timo Freiesleben, Philipp Berens
2024 — conf
Interpretable-by-Design Deep Survival Analysis for Disease Progression Modeling.
MICCAI (10)
Julius Gervelmeyer, Sarah Müller, Kerol Djoumessi, David Merle, Simon J. Clark, Lisa M. Koch, Philipp Berens
2024 — conf
Leveraging Probabilistic Segmentation Models for Improved Glaucoma Diagnosis: A Clinical Pipeline Approach.
MIDL
Anna M. Wundram, Paul Fischer, Stephan Wunderlich, Hanna Faber, Lisa M. Koch, Philipp Berens, Christian F. Baumgartner
2024 J jnl
Meet the authors: Rita González-Márquez, Philipp Berens, and Dmitry Kobak.
Patterns
Rita González-Márquez, Philipp Berens, Dmitry Kobak
2024 A* conf
Most discriminative stimuli for functional cell type clustering.
ICLR
Max F. Burg, Thomas Zenkel, Michaela Vystrcilová, Jonathan Oesterle, Larissa Höfling, Konstantin F. 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
2024 J jnl
Most discriminative stimuli for functional cell type identification.
CoRR
Max F. Burg, Thomas Zenkel, Michaela Vystrcilová, Jonathan Oesterle, Larissa Höfling, Konstantin F. 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
2024 A* conf
Persistent Homology for High-dimensional Data Based on Spectral Methods.
NeurIPS
Sebastian Damrich, Philipp Berens, Dmitry Kobak
2024 J jnl
Self-supervised Visualisation of Medical Image Datasets.
CoRR
Ifeoma Veronica Nwabufo, Jan Niklas Böhm, Philipp Berens, Dmitry Kobak
2024 J jnl
The art of seeing the elephant in the room: 2D embeddings of single-cell data do make sense.
PLoS Comput. Biol.
Jan Lause, Philipp Berens, Dmitry Kobak
2024 J jnl
The landscape of biomedical research.
Patterns
Rita González-Márquez, Luca Schmidt, Benjamin M. Schmidt, Philipp Berens, Dmitry Kobak
2024 — conf
This Actually Looks Like that: Proto-BagNets for Local and Global Interpretability-by-Design.
MICCAI (10)
Kerol Djoumessi, Bubacarr Bah, Laura Kühlewein, Philipp Berens, Lisa M. Koch
2024 J jnl
This actually looks like that: Proto-BagNets for local and global interpretability-by-design.
CoRR
Kerol Djoumessi, Bubacarr Bah, Laura Kühlewein, Philipp Berens, Lisa M. Koch
2023 J jnl
AI for Science: An Emerging Agenda.
CoRR
Philipp Berens, Kyle Cranmer, Neil D. Lawrence, Ulrike von Luxburg, Jessica Montgomery
2023 J jnl
Deep Hypothesis Tests Detect Clinically Relevant Subgroup Shifts in Medical Images.
CoRR
Lisa M. Koch, Christian M. Schürch, Christian F. Baumgartner, Arthur Gretton, Philipp Berens
2023 J jnl
Generating Realistic Counterfactuals for Retinal Fundus and OCT Images using Diffusion Models.
CoRR
Indu Ilanchezian, Valentyn Boreiko, Laura Kühlewein, Ziwei Huang, Murat Seçkin Ayhan, Matthias Hein, Lisa M. Koch, Philipp Berens
2023 J jnl
Persistent homology for high-dimensional data based on spectral methods.
CoRR
Sebastian Damrich, Philipp Berens, Dmitry Kobak
2023 — conf
Sparse Activations for Interpretable Disease Grading.
MIDL
Kerol R. Djoumessi Donteu, Indu Ilanchezian, Laura Kühlewein, Hanna Faber, Christian F. Baumgartner, Bubacarr Bah, Philipp Berens, Lisa M. Koch
2023 A* conf
Unsupervised visualization of image datasets using contrastive learning.
ICLR
Jan Niklas Böhm, Philipp Berens, Dmitry Kobak
2022 J jnl
Attraction-Repulsion Spectrum in Neighbor Embeddings.
J. Mach. Learn. Res.
Jan Niklas Böhm, Philipp Berens, Dmitry Kobak
2022 J jnl
Clinical validation of saliency maps for understanding deep neural networks in ophthalmology.
Medical Image Anal.
Murat Seçkin Ayhan, Louis Benedikt Kümmerle, Laura Kühlewein, Werner Inhoffen, Gulnar Aliyeva, Focke Ziemssen, Philipp Berens
2022 J jnl
Correction to: Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models.
J. Comput. Neurosci.
Jonathan Oesterle, Nicholas Krämer, Philipp Hennig, Philipp Berens
2022 A* conf
Efficient identification of informative features in simulation-based inference.
NeurIPS
Jonas Beck, Michael Deistler, Yves Bernaerts, Jakob H. Macke, Philipp Berens
2022 J jnl
Efficient identification of informative features in simulation-based inference.
CoRR
Jonas Beck, Michael Deistler, Yves Bernaerts, Jakob H. Macke, Philipp Berens
2022 — conf
Hidden in Plain Sight: Subgroup Shifts Escape OOD Detection.
MIDL
Lisa M. Koch, Christian M. Schürch, Arthur Gretton, Philipp Berens
2022 J jnl
Hierarchical mixtures of Gaussians for combined dimensionality reduction and clustering.
CoRR
Sacha Sokoloski, Philipp Berens
2022 J jnl
Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling (Dagstuhl Seminar 22382).
Dagstuhl Reports
Philipp Berens, Kyle Cranmer, Neil D. Lawrence, Ulrike von Luxburg, Jessica Montgomery
2022 J jnl
Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models.
J. Comput. Neurosci.
Jonathan Oesterle, Nicholas Krämer, Philipp Hennig, Philipp Berens
2022 — conf
Sparse Visual Counterfactual Explanations in Image Space.
GCPR
Valentyn Boreiko, Maximilian Augustin, Francesco Croce, Philipp Berens, Matthias Hein
2022 J jnl
Sparse Visual Counterfactual Explanations in Image Space.
CoRR
Valentyn Boreiko, Maximilian Augustin, Francesco Croce, Philipp Berens, Matthias Hein
2022 — conf
Two-dimensional visualization of large document libraries using t-SNE.
TAG-ML
Rita González-Márquez, Philipp Berens, Dmitry Kobak
2022 J jnl
Unsupervised visualization of image datasets using contrastive learning.
CoRR
Jan Niklas Böhm, Philipp Berens, Dmitry Kobak
2022 — conf
Visual Explanations for the Detection of Diabetic Retinopathy from Retinal Fundus Images.
MICCAI (2)
Valentyn Boreiko, Indu Ilanchezian, Murat Seçkin Ayhan, Sarah Müller, Lisa M. Koch, Hanna Faber, Philipp Berens, Matthias Hein
2021 J jnl
Estimating smooth and sparse neural receptive fields with a flexible spline basis.
CoRR
Ziwei Huang, Yanli Ran, Jonathan Oesterle, Thomas Euler, Philipp Berens
2021 — conf
Interpretable Gender Classification from Retinal Fundus Images Using BagNets.
MICCAI (3)
Indu Ilanchezian, Dmitry Kobak, Hanna Faber, Focke Ziemssen, Philipp Berens, Murat Seçkin Ayhan
2021 A* conf
MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space.
ICML
Sophie Laturnus, Philipp Berens
2021 A* conf
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience.
NeurIPS
Dominic Gonschorek, Larissa Höfling, Klaudia P. Szatko, Katrin Franke, Timm Schubert, Benjamin A. Dunn, Philipp Berens, David A. Klindt, Thomas Euler
2020 J jnl
A Systematic Evaluation of Interneuron Morphology Representations for Cell Type Discrimination.
Neuroinformatics
Sophie Laturnus, Dmitry Kobak, Philipp Berens
2020 J jnl
A Unifying Perspective on Neighbor Embeddings along the Attraction-Repulsion Spectrum.
CoRR
Jan Niklas Böhm, Philipp Berens, Dmitry Kobak
2020 J jnl
Expert-validated estimation of diagnostic uncertainty for deep neural networks in diabetic retinopathy detection.
Medical Image Anal.
Murat Seçkin Ayhan, Laura Kühlewein, Gulnar Aliyeva, Werner Inhoffen, Focke Ziemssen, Philipp Berens
2020 J jnl
MorphoPy: A python package for feature extraction of neural morphologies.
J. Open Source Softw.
Sophie Laturnus, Adam von Daranyi, Ziwei Huang, Philipp Berens
2020 J jnl
Sparse Bottleneck Networks for Exploratory Analysis and Visualization of Neural Patch-seq Data.
CoRR
Yves Bernaerts, Philipp Berens, Dmitry Kobak
2020 A* conf
System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina.
NeurIPS
Cornelius Schröder, David A. Klindt, Sarah Strauß, Katrin Franke, Matthias Bethge, Thomas Euler, Philipp Berens
2019 A* conf
Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse.
NeurIPS
Cornelius Schröder, Ben James, Leon Lagnado, Philipp Berens
2019 J jnl
Bayesian hypothesis testing and experimental design for two-photon imaging data.
PLoS Comput. Biol.
Luke E. Rogerson, Zhijian Zhao, Katrin Franke, Thomas Euler, Philipp Berens
2019 J jnl
Correction: Bayesian hypothesis testing and experimental design for two-photon imaging data.
PLoS Comput. Biol.
Luke E. Rogerson, Zhijian Zhao, Katrin Franke, Thomas Euler, Philipp Berens
2019 — conf
Heavy-Tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations.
ECML/PKDD (1)
Dmitry Kobak, George C. Linderman, Stefan Steinerberger, Yuval Kluger, Philipp Berens
2019 J jnl
Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations.
CoRR
Dmitry Kobak, George C. Linderman, Stefan Steinerberger, Yuval Kluger, Philipp Berens
2018 J jnl
Community-based benchmarking improves spike rate inference from two-photon calcium imaging data.
PLoS Comput. Biol.
Philipp Berens, Jeremy Freeman, Thomas Deneux, Nicolay Chenkov, Thomas McColgan, Artur Speiser, Jakob H. Macke, Srinivas C. Turaga, Patrick J. Mineault, Peter Rupprecht, Stephan Gerhard, Rainer W. Friedrich, Johannes Friedrich, Liam Paninski, Marius Pachitariu, Kenneth D. Harris, Ben Bolte, Timothy A. Machado, Dario Ringach, Jasmine Stone, Luke E. Rogerson, Nicolas J. Sofroniew, Jacob Reimer, Emmanouil Froudarakis, Thomas Euler, Miroslav Román Rosón, Lucas Theis, Andreas S. Tolias, Matthias Bethge
2017 J jnl
Signatures of criticality arise from random subsampling in simple population models.
PLoS Comput. Biol.
Marcel Nonnenmacher, Christian Behrens, Philipp Berens, Matthias Bethge, Jakob H. Macke
2016 J jnl
The functional diversity of retinal ganglion cells in the mouse.
Nat.
Tom Baden, Philipp Berens, Katrin Franke, Miroslav Román Rosón, Matthias Bethge, Thomas Euler
2011 J jnl
Statistical Analysis of Multi-Cell Recordings: Linking Population Coding Models to Experimental Data.
Frontiers Comput. Neurosci.
Jakob H. Macke, Philipp Berens, Matthias Bethge
2009 — conf
A joint maximum-entropy model for binary neural population patterns and continuous signals.
NIPS
Sebastian Gerwinn, Philipp Berens, Matthias Bethge
2009 J jnl
Generating Spike Trains with Specified Correlation Coefficients.
Neural Comput.
Jakob H. Macke, Philipp Berens, Alexander S. Ecker, Andreas S. Tolias, Matthias Bethge
2009 — conf
Neurometric function analysis of population codes.
NIPS
Philipp Berens, Sebastian Gerwinn, Alexander S. Ecker, Matthias Bethge
2007 — conf
Near-Maximum Entropy Models for Binary Neural Representations of Natural Images.
NIPS
Matthias Bethge, Philipp Berens