Matthias Bethge

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 126

Top Venues

CoRR

ICLR

NeurIPS

PLoS Comput. Biol.

Publications

Mark Basting, Robert-Jan Bruintjes, Thaddäus Wiedemer, Matthias Kümmerer, Matthias Bethge, Jan van Gemert
Scale Learning in Scale-Equivariant Convolutional Networks. VISIGRAPP (2): VISAPP (2024)
Çagatay Yildiz, Nishaanth Kanna Ravichandran, Prishruit Punia, Matthias Bethge, Beyza Ermis
Investigating Continual Pretraining in Large Language Models: Insights and Implications. CoRR (2024)
Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel
Does CLIP's generalization performance mainly stem from high train-test similarity? ICLR (2024)
Çaglar Hizli, Çagatay Yildiz, Matthias Bethge, St John, Pekka Marttinen
Identifying latent state transition in non-linear dynamical systems. CoRR (2024)
Vishaal Udandarao, Ameya Prabhu, Adhiraj Ghosh, Yash Sharma, Philip H. S. Torr, Adel Bibi, Samuel Albanie, Matthias Bethge
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance. CoRR (2024)
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
Most discriminative stimuli for functional cell type clustering. ICLR (2024)
Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel
Provable Compositional Generalization for Object-Centric Learning. ICLR (2024)
Eli Verwimp, Rahaf Aljundi, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven
Continual Learning: Applications and the Road Forward. Trans. Mach. Learn. Res. 2024 (2024)
Lukas Thede, Karsten Roth, Olivier J. Hénaff, Matthias Bethge, Zeynep Akata
Reflecting on the State of Rehearsal-free Continual Learning with Pretrained Models. CoRR (2024)
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
Most discriminative stimuli for functional cell type identification. CoRR (2024)
Ameya Prabhu, Vishaal Udandarao, Philip H. S. Torr, Matthias Bethge, Adel Bibi, Samuel Albanie
Lifelong Benchmarks: Efficient Model Evaluation in an Era of Rapid Progress. CoRR (2024)
Vishaal Udandarao, Max F. Burg, Samuel Albanie, Matthias Bethge
Visual Data-Type Understanding does not emerge from scaling Vision-Language Models. ICLR (2024)
Ori Press, Andreas Hochlehnert, Ameya Prabhu, Vishaal Udandarao, Ofir Press, Matthias Bethge
CiteME: Can Language Models Accurately Cite Scientific Claims? CoRR (2024)
Ori Press, Ravid Shwartz-Ziv, Yann LeCun, Matthias Bethge
The Entropy Enigma: Success and Failure of Entropy Minimization. CoRR (2024)
Shiven Sinha, Ameya Prabhu, Ponnurangam Kumaraguru, Siddharth Bhat, Matthias Bethge
Wu's Method can Boost Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO Geometry. CoRR (2024)
Eli Verwimp, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven
Continual Learning: Applications and the Road Forward. CoRR (2023)
Yongrong Qiu, David A. Klindt, Klaudia P. Szatko, Dominic Gonschorek, Larissa Höfling, Timm Schubert, Laura Busse, Matthias Bethge, Thomas Euler
Efficient coding of natural scenes improves neural system identification. PLoS Comput. Biol. 19 (4) (2023)
Elif Akata, Lion Schulz, Julian Coda-Forno, Seong Joon Oh, Matthias Bethge, Eric Schulz
Playing repeated games with Large Language Models. CoRR (2023)
Zhe Li, Josue Ortega Caro, Evgenia Rusak, Wieland Brendel, Matthias Bethge, Fabio Anselmi, Ankit B. Patel, Andreas S. Tolias, Xaq Pitkow
Robust deep learning object recognition models rely on low frequency information in natural images. PLoS Comput. Biol. 19 (3) (2023)
Ilze Amanda Auzina, Çagatay Yildiz, Sara Magliacane, Matthias Bethge, Efstratios Gavves
Invariant Neural Ordinary Differential Equations. CoRR (2023)
Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel
Compositional Generalization from First Principles. NeurIPS (2023)
Sebastian Dziadzio, Çagatay Yildiz, Gido M. van de Ven, Tomasz Trzcinski, Tinne Tuytelaars, Matthias Bethge
Disentangled Continual Learning: Separating Memory Edits from Model Updates. CoRR (2023)
Luca M. Schulze Buschoff, Elif Akata, Matthias Bethge, Eric Schulz
Have we built machines that think like people? CoRR (2023)
Ori Press, Steffen Schneider, Matthias Kümmerer, Matthias Bethge
RDumb: A simple approach that questions our progress in continual test-time adaptation. CoRR (2023)
Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel
Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity? CoRR (2023)
Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel
Jacobian-based Causal Discovery with Nonlinear ICA. Trans. Mach. Learn. Res. 2023 (2023)
Ilze Amanda Auzina, Çagatay Yildiz, Sara Magliacane, Matthias Bethge, Efstratios Gavves
Modulated Neural ODEs. NeurIPS (2023)
Ori Press, Steffen Schneider, Matthias Kümmerer, Matthias Bethge
RDumb: A simple approach that questions our progress in continual test-time adaptation. NeurIPS (2023)
Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel
Provable Compositional Generalization for Object-Centric Learning. CoRR (2023)
Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, Bernhard Schölkopf
Unsupervised Object Learning via Common Fate. CLeaR (2023)
Vishaal Udandarao, Max F. Burg, Samuel Albanie, Matthias Bethge
Visual Data-Type Understanding does not emerge from Scaling Vision-Language Models. CoRR (2023)
Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel
Compositional Generalization from First Principles. CoRR (2023)
Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter Vincent Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. ICLR (2022)
Evgenia Rusak, Steffen Schneider, George Pachitariu, Luisa Eck, Peter Vincent Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge
If your data distribution shifts, use self-learning. Trans. Mach. Learn. Res. 2022 (2022)
Christina M. Funke, Paul Vicol, Kuan-Chieh Wang, Matthias Kümmerer, Richard S. Zemel, Matthias Bethge
Disentanglement and Generalization Under Correlation Shifts. CoLLAs (2022)
Judy Borowski, Roland Simon Zimmermann, Judith Schepers, Robert Geirhos, Thomas S. A. Wallis, Matthias Bethge, Wieland Brendel
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization. ICLR (2021)
Marissa A. Weis, Kashyap Chitta, Yash Sharma, Wieland Brendel, Matthias Bethge, Andreas Geiger, Alexander S. Ecker
Benchmarking Unsupervised Object Representations for Video Sequences. J. Mach. Learn. Res. 22 (2021)
Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter V. Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. CoRR (2021)
Akis Linardos, Matthias Kümmerer, Ori Press, Matthias Bethge
Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling. CoRR (2021)
Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel
Contrastive Learning Inverts the Data Generating Process. ICML (2021)
Evgenia Rusak, Steffen Schneider, Peter V. Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge
Adapting ImageNet-scale models to complex distribution shifts with self-learning. CoRR (2021)
Alexander Mathis, Thomas Biasi, Steffen Schneider, Mert Yüksekgönül, Byron Rogers, Matthias Bethge, Mackenzie W. Mathis
Pretraining boosts out-of-domain robustness for pose estimation. WACV (2021)
Christina M. Funke, Paul Vicol, Kuan-Chieh Wang, Matthias Kümmerer, Richard S. Zemel, Matthias Bethge
Disentanglement and Generalization Under Correlation Shifts. CoRR (2021)
Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel
Contrastive Learning Inverts the Data Generating Process. CoRR (2021)
Max F. Burg, Santiago A. Cadena, George H. Denfield, Edgar Y. Walker, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker
Learning divisive normalization in primary visual cortex. PLoS Comput. Biol. 17 (6) (2021)
David A. Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan M. Paiton
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding. ICLR (2021)
Akis Linardos, Matthias Kümmerer, Ori Press, Matthias Bethge
DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling. ICCV (2021)
Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Tizian Thieringer, Matthias Bethge, Felix A. Wichmann, Wieland Brendel
Partial success in closing the gap between human and machine vision. CoRR (2021)
Roland S. Zimmermann, Judy Borowski, Robert Geirhos, Matthias Bethge, Thomas S. A. Wallis, Wieland Brendel
How Well do Feature Visualizations Support Causal Understanding of CNN Activations? CoRR (2021)
Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter V. Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, Bernhard Schölkopf
Unsupervised Object Learning via Common Fate. CoRR (2021)
Roland S. Zimmermann, Judy Borowski, Robert Geirhos, Matthias Bethge, Thomas S. A. Wallis, Wieland Brendel
How Well do Feature Visualizations Support Causal Understanding of CNN Activations? NeurIPS (2021)
Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Tizian Thieringer, Matthias Bethge, Felix A. Wichmann, Wieland Brendel
Partial success in closing the gap between human and machine vision. NeurIPS (2021)
Matthias Kümmerer, Matthias Bethge
State-of-the-Art in Human Scanpath Prediction. CoRR (2021)
Marissa A. Weis, Kashyap Chitta, Yash Sharma, Wieland Brendel, Matthias Bethge, Andreas Geiger, Alexander S. Ecker
Unmasking the Inductive Biases of Unsupervised Object Representations for Video Sequences. CoRR (2020)
Claudio Michaelis, Matthias Bethge, Alexander S. Ecker
Closing the Generalization Gap in One-Shot Object Detection. CoRR (2020)
Matthias Tangemann, Matthias Kümmerer, Thomas S. A. Wallis, Matthias Bethge
Measuring the Importance of Temporal Features in Video Saliency. ECCV (28) (2020)
Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge
Improving robustness against common corruptions by covariate shift adaptation. CoRR (2020)
Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge
Improving robustness against common corruptions by covariate shift adaptation. NeurIPS (2020)
Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Matthias Bethge, Felix A. Wichmann, Wieland Brendel
On the surprising similarities between supervised and self-supervised models. CoRR (2020)
Jonas Rauber, Matthias Bethge, Wieland Brendel
EagerPy: Writing Code That Works Natively with PyTorch, TensorFlow, JAX, and NumPy. CoRR (2020)
Cornelius Schröder, David Klindt, Sarah Strauß, Katrin Franke, Matthias Bethge, Thomas Euler, Philipp Berens
System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina. NeurIPS (2020)
Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel
Increasing the robustness of DNNs against image corruptions by playing the Game of Noise. CoRR (2020)
Ivan Ustyuzhaninov, Santiago A. Cadena, Emmanouil Froudarakis, Paul G. Fahey, Edgar Y. Walker, Erick Cobos, Jacob Reimer, Fabian H. Sinz, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker
Rotation-invariant clustering of neuronal responses in primary visual cortex. ICLR (2020)
Ute Schmid, Volker Tresp, Matthias Bethge, Kristian Kersting, Rainer Stiefelhagen
Künstliche Intelligenz - Die dritte Welle. GI-Jahrestagung (2020)
Jonas Rauber, Roland Zimmermann, Matthias Bethge, Wieland Brendel
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX. J. Open Source Softw. 5 (53) (2020)
David Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan M. Paiton
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding. CoRR (2020)
Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard S. Zemel, Wieland Brendel, Matthias Bethge, Felix A. Wichmann
Shortcut learning in deep neural networks. Nat. Mach. Intell. 2 (11) (2020)
Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel
A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions. ECCV (3) (2020)
Jonas Rauber, Matthias Bethge
Fast Differentiable Clipping-Aware Normalization and Rescaling. CoRR (2020)
Judy Borowski, Roland S. Zimmermann, Judith Schepers, Robert Geirhos, Thomas S. A. Wallis, Matthias Bethge, Wieland Brendel
Exemplary Natural Images Explain CNN Activations Better than Feature Visualizations. CoRR (2020)
Julius von Kügelgen, Ivan Ustyuzhaninov, Peter V. Gehler, Matthias Bethge, Bernhard Schölkopf
Towards causal generative scene models via competition of experts. CoRR (2020)
Christina M. Funke, Judy Borowski, Karolina Stosio, Wieland Brendel, Thomas S. A. Wallis, Matthias Bethge
The Notorious Difficulty of Comparing Human and Machine Perception. CoRR (2020)
Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard S. Zemel, Wieland Brendel, Matthias Bethge, Felix A. Wichmann
Shortcut Learning in Deep Neural Networks. CoRR (2020)
Lukas Schott, Jonas Rauber, Matthias Bethge, Wieland Brendel
Towards the first adversarially robust neural network model on MNIST. ICLR (Poster) (2019)
Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A. Wichmann, Wieland Brendel
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness. ICLR (2019)
Claudio Michaelis, Benjamin Mitzkus, Robert Geirhos, Evgenia Rusak, Oliver Bringmann, Alexander S. Ecker, Matthias Bethge, Wieland Brendel
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming. CoRR (2019)
Alexander S. Ecker, Fabian H. Sinz, Emmanouil Froudarakis, Paul G. Fahey, Santiago A. Cadena, Edgar Y. Walker, Erick Cobos, Jacob Reimer, Andreas S. Tolias, Matthias Bethge
A rotation-equivariant convolutional neural network model of primary visual cortex. ICLR (Poster) (2019)
Zhe Li, Wieland Brendel, Edgar Y. Walker, Erick Cobos, Taliah Muhammad, Jacob Reimer, Matthias Bethge, Fabian H. Sinz, Xaq Pitkow, Andreas S. Tolias
Learning From Brains How to Regularize Machines. CoRR (2019)
Zhe Li, Wieland Brendel, Edgar Y. Walker, Erick Cobos, Taliah Muhammad, Jacob Reimer, Matthias Bethge, Fabian H. Sinz, Zachary Pitkow, Andreas S. Tolias
Learning from brains how to regularize machines. NeurIPS (2019)
Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge
Accurate, reliable and fast robustness evaluation. CoRR (2019)
Wieland Brendel, Matthias Bethge
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet. CoRR (2019)
Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge
Accurate, reliable and fast robustness evaluation. NeurIPS (2019)
Santiago A. Cadena, George H. Denfield, Edgar Y. Walker, Leon A. Gatys, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker
Deep convolutional models improve predictions of macaque V1 responses to natural images. PLoS Comput. Biol. 15 (4) (2019)
Jörn-Henrik Jacobsen, Jens Behrmann, Richard S. Zemel, Matthias Bethge
Excessive Invariance Causes Adversarial Vulnerability. ICLR (Poster) (2019)
Wieland Brendel, Matthias Bethge
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet. ICLR (Poster) (2019)
Alexander Mathis, Mert Yüksekgönül, Byron Rogers, Matthias Bethge, Mackenzie W. Mathis
Pretraining boosts out-of-domain robustness for pose estimation. CoRR (2019)
Alexander Böttcher, Wieland Brendel, Bernhard Englitz, Matthias Bethge
Trace your sources in large-scale data: one ring to find them all. CoRR (2018)
Alexander Mathis, Pranav Mamidanna, Taiga Abe, Kevin M. Cury, Venkatesh N. Murthy, Mackenzie W. Mathis, Matthias Bethge
Markerless tracking of user-defined features with deep learning. CoRR (2018)
Lukas Schott, Jonas Rauber, Wieland Brendel, Matthias Bethge
Robust Perception through Analysis by Synthesis. CoRR (2018)
Robert Geirhos, Carlos R. Medina Temme, Jonas Rauber, Heiko H. Schütt, Matthias Bethge, Felix A. Wichmann
Generalisation in humans and deep neural networks. NeurIPS (2018)
Claudio Michaelis, Ivan Ustyuzhaninov, Matthias Bethge, Alexander S. Ecker
One-Shot Instance Segmentation. CoRR (2018)
Ivan Ustyuzhaninov, Claudio Michaelis, Wieland Brendel, Matthias Bethge
One-shot Texture Segmentation. CoRR (2018)
Santiago A. Cadena, Marissa A. Weis, Leon A. Gatys, Matthias Bethge, Alexander S. Ecker
Diverse Feature Visualizations Reveal Invariances in Early Layers of Deep Neural Networks. ECCV (12) (2018)
Alexander S. Ecker, Fabian H. Sinz, Emmanouil Froudarakis, Paul G. Fahey, Santiago A. Cadena, Edgar Y. Walker, Erick Cobos, Jacob Reimer, Andreas S. Tolias, Matthias Bethge
A rotation-equivariant convolutional neural network model of primary visual cortex. CoRR (2018)
Wieland Brendel, Jonas Rauber, Matthias Bethge
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models. ICLR (Poster) (2018)
Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge
Adversarial Vision Challenge. CoRR (2018)
Matthias Kümmerer, Thomas S. A. Wallis, Matthias Bethge
Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics. ECCV (16) (2018)
Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A. Wichmann, Wieland Brendel
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness. CoRR (2018)
Jörn-Henrik Jacobsen, Jens Behrmann, Richard S. Zemel, Matthias Bethge
Excessive Invariance Causes Adversarial Vulnerability. CoRR (2018)
Claudio Michaelis, Matthias Bethge, Alexander S. Ecker
One-Shot Segmentation in Clutter. CoRR (2018)

Matthias Bethge.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Matthias Bethge