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State-of-the-Art in Human Scanpath Prediction


Feb 24, 2021
Matthias Kümmerer, Matthias Bethge


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Contrastive Learning Inverts the Data Generating Process


Feb 17, 2021
Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel

* The first three authors, as well as the last two authors, contributed equally. Code is available at https://brendel-group.github.io/cl-ica 

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Closing the Generalization Gap in One-Shot Object Detection


Nov 09, 2020
Claudio Michaelis, Matthias Bethge, Alexander S. Ecker


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Exemplary Natural Images Explain CNN Activations Better than Feature Visualizations


Oct 23, 2020
Judy Borowski, Roland S. Zimmermann, Judith Schepers, Robert Geirhos, Thomas S. A. Wallis, Matthias Bethge, Wieland Brendel


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On the surprising similarities between supervised and self-supervised models


Oct 16, 2020
Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Matthias Bethge, Felix A. Wichmann, Wieland Brendel


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EagerPy: Writing Code That Works Natively with PyTorch, TensorFlow, JAX, and NumPy


Aug 10, 2020
Jonas Rauber, Matthias Bethge, Wieland Brendel


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Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding


Jul 21, 2020
David Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan Paiton

* Code is available at https://github.com/bethgelab/slow_disentanglement. The first three authors, as well as the last two authors, contributed equally 

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Fast Differentiable Clipping-Aware Normalization and Rescaling


Jul 15, 2020
Jonas Rauber, Matthias Bethge


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Improving robustness against common corruptions by covariate shift adaptation


Jun 30, 2020
Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge


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Unmasking the Inductive Biases of Unsupervised Object Representations for Video Sequences


Jun 12, 2020
Marissa A. Weis, Kashyap Chitta, Yash Sharma, Wieland Brendel, Matthias Bethge, Andreas Geiger, Alexander S. Ecker


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Shortcut Learning in Deep Neural Networks


May 20, 2020
Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard Zemel, Wieland Brendel, Matthias Bethge, Felix A. Wichmann

* perspective article 

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Towards causal generative scene models via competition of experts


Apr 27, 2020
Julius von Kügelgen, Ivan Ustyuzhaninov, Peter Gehler, Matthias Bethge, Bernhard Schölkopf

* Presented at the ICLR 2020 workshop "Causal learning for decision making" 

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The Notorious Difficulty of Comparing Human and Machine Perception


Apr 20, 2020
Christina M. Funke, Judy Borowski, Karolina Stosio, Wieland Brendel, Thomas S. A. Wallis, Matthias Bethge


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Increasing the robustness of DNNs against image corruptions by playing the Game of Noise


Feb 26, 2020
Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel


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Learning From Brains How to Regularize Machines


Nov 11, 2019
Zhe Li, Wieland Brendel, Edgar Y. Walker, Erick Cobos, Taliah Muhammad, Jacob Reimer, Matthias Bethge, Fabian H. Sinz, Xaq Pitkow, Andreas S. Tolias

* 14 pages, 7 figures, NeurIPS 2019 

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Pretraining boosts out-of-domain robustness for pose estimation


Sep 24, 2019
Alexander Mathis, Mert Yüksekgönül, Byron Rogers, Matthias Bethge, Mackenzie W. Mathis


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Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming


Jul 17, 2019
Claudio Michaelis, Benjamin Mitzkus, Robert Geirhos, Evgenia Rusak, Oliver Bringmann, Alexander S. Ecker, Matthias Bethge, Wieland Brendel

* 23 pages, 10 figures, 1 dragon 

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Accurate, reliable and fast robustness evaluation


Jul 01, 2019
Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge


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Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet


Mar 20, 2019
Wieland Brendel, Matthias Bethge

* Published as a conference paper at the Seventh International Conference on Learning Representations (ICLR 2019) 

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ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness


Nov 29, 2018
Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A. Wichmann, Wieland Brendel

* Under review at ICLR 2019 (review scores 8,8,7) 

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One-Shot Instance Segmentation


Nov 28, 2018
Claudio Michaelis, Ivan Ustyuzhaninov, Matthias Bethge, Alexander S. Ecker


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Excessive Invariance Causes Adversarial Vulnerability


Nov 01, 2018
Jörn-Henrik Jacobsen, Jens Behrmann, Richard Zemel, Matthias Bethge


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A rotation-equivariant convolutional neural network model of primary visual cortex


Sep 27, 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


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Towards the first adversarially robust neural network model on MNIST


Sep 20, 2018
Lukas Schott, Jonas Rauber, Matthias Bethge, Wieland Brendel


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Generalisation in humans and deep neural networks


Aug 27, 2018
Robert Geirhos, Carlos R. Medina Temme, Jonas Rauber, Heiko H. Schuett, Matthias Bethge, Felix A. Wichmann

* Submitted to NIPS 2018. 26 pages, 14 figures, 1 table. Supersedes and greatly extends arXiv:1706.06969 

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Adversarial Vision Challenge


Aug 06, 2018
Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge

* https://www.crowdai.org/challenges/adversarial-vision-challenge 

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