2023
Reizinger, P., Sharma, Y., Bethge, M., Schölkopf, B., Huszár, F., Brendel, W.
Jacobian-based Causal Discovery with Nonlinear ICA
Transactions on Machine Learning Research, April 2023 (article)
2022
Zimmermann, Roland S, Brendel, Wieland, Tramer, Florian, Carlini, Nicholas
Increasing Confidence in Adversarial Robustness Evaluations
arXiv preprint arXiv:2206.13991, 2022 (article)
Reizinger, Patrik, Gresele, Luigi, Brady, Jack, von Kügelgen, Julius, Zietlow, Dominik, Schölkopf, Bernhard, Martius, Georg, Brendel, Wieland, Besserve, Michel
Embrace the Gap: VAEs Perform Independent Mechanism Analysis
arXiv preprint arXiv:2206.02416, 2022 (article)
Li, Zhe, Caro, Josue Ortega, Rusak, Evgenia, Brendel, Wieland, Bethge, Matthias, Anselmi, Fabio, Patel, Ankit B, Tolias, Andreas S, Pitkow, Xaq
Robust deep learning object recognition models rely on low frequency information in natural images
bioRxiv, Cold Spring Harbor Laboratory, 2022 (article)
2021
Funke, Christina M, Borowski, Judy, Stosio, Karolina, Brendel, Wieland, Wallis, Thomas SA, Bethge, Matthias
Five points to check when comparing visual perception in humans and machines
Journal of Vision, 21(3):16-16, The Association for Research in Vision and Ophthalmology, 2021 (article)
Rusak, Evgenia, Schneider, Steffen, Pachitariu, George, Eck, Luisa, Gehler, Peter Vincent, Bringmann, Oliver, Brendel, Wieland, Bethge, Matthias
If your data distribution shifts, use self-learning
2021 (article)
Rusak, Evgenia, Schneider, Steffen, Gehler, Peter, Bringmann, Oliver, Brendel, Wieland, Bethge, Matthias
Adapting ImageNet-scale models to complex distribution shifts with self-learning
arXiv preprint arXiv:2104.12928, 2021 (article)
2020
Schneider123, Steffen, Krishna, Shubham, Eck, Luisa, Brendel, Wieland, Mathis, Mackenzie W, Bethge, Matthias
Generalized Invariant Risk Minimization: relating adaptation and invariant representation learning
2020 (article)
Brendel, Wieland, Bourdoukan, Ralph, Vertechi, Pietro, Machens, Christian K, Denéve, Sophie
Learning to represent signals spike by spike
PLoS computational biology, 16(3):e1007692, Public Library of Science San Francisco, CA USA, 2020 (article)
Rauber, Jonas, Bethge, Matthias, Brendel, Wieland
EagerPy: Writing code that works natively with PyTorch, TensorFlow, JAX, and NumPy
arXiv preprint arXiv:2008.04175, 2020 (article)
Ortega Caro, Josue, Ju, Yilong, Pyle, Ryan, Dey, Sourav, Brendel, Wieland, Anselmi, Fabio, Patel, Ankit
Local Convolutions Cause an Implicit Bias towards High Frequency Adversarial Examples
arXiv e-prints, pages: arXiv-2006, 2020 (article)
Geirhos, Robert, Jacobsen, Jörn-Henrik, Michaelis, Claudio, Zemel, Richard, Brendel, Wieland, Bethge, Matthias, Wichmann, Felix A
Shortcut Learning in Deep Neural Networks
Nature Machine Intelligence volume 2, pages665--673(2020), 2020 (article)
Caro, Josue Ortega, Ju, Yilong, Pyle, Ryan, Dey, Sourav, Brendel, Wieland, Anselmi, Fabio, Patel, Ankit
Local convolutions cause an implicit bias towards high frequency adversarial examples
arXiv preprint arXiv:2006.11440, 2020 (article)
Weis, Marissa A, Chitta, Kashyap, Sharma, Yash, Brendel, Wieland, Bethge, Matthias, Geiger, Andreas, Ecker, Alexander S
Unmasking the inductive biases of unsupervised object representations for video sequences
Journal of Machine Learning Research (JMLR), 2020 (article)
Rauber, Jonas, Zimmermann, Roland, Bethge, Matthias, Brendel, Wieland
Foolbox native: Fast adversarial attacks to benchmark the robustness of machine learning models in pytorch, tensorflow, and jax
Journal of Open Source Software, 5(53):2607, 2020 (article)
2019
Carlini, Nicholas, Athalye, Anish, Papernot, Nicolas, Brendel, Wieland, Rauber, Jonas, Tsipras, Dimitris, Goodfellow, Ian, Madry, Aleksander, Kurakin, Alexey
On evaluating adversarial robustness
arXiv preprint arXiv:1902.06705, 2019 (article)
2018
Böttcher, Alexander, Brendel, Wieland, Englitz, Bernhard, Bethge, Matthias
Trace your sources in large-scale data: one ring to find them all
arXiv preprint arXiv:1803.08882, 2018 (article)
Funke, Christina, Borowski, Judy, Wallis, Thomas, Brendel, Wieland, Ecker, Alexander, Bethge, Matthias
Comparing the ability of humans and DNNs to recognise closed contours in cluttered images
Journal of Vision, 18(10):800-800, The Association for Research in Vision and Ophthalmology, 2018 (article)
Oladazimi, Maysam, Brendel, Wieland, Schwarz, Cornelius
Biomechanical texture coding in rat whiskers
Scientific reports, 8(1):1-12, Nature Publishing Group, 2018 (article)
Ustyuzhaninov, Ivan, Michaelis, Claudio, Brendel, Wieland, Bethge, Matthias
One-shot texture segmentation
arXiv preprint arXiv:1807.02654, 2018 (article)
2017
Brendel, Wieland, Bethge, Matthias
Comment on" Biologically inspired protection of deep networks from adversarial attacks"
arXiv preprint arXiv:1704.01547, 2017 (article)
2016
Kobak, Dmitry, Brendel, Wieland, Constantinidis, Christos, Feierstein, Claudia E, Kepecs, Adam, Mainen, Zachary F, Qi, Xue-Lian, Romo, Ranulfo, Uchida, Naoshige, Machens, Christian K
Demixed principal component analysis of neural population data
Elife, 5, pages: e10989, eLife Sciences Publications Limited, 2016 (article)
Ustyuzhaninov, Ivan, Brendel, Wieland, Gatys, Leon A, Bethge, Matthias
Texture synthesis using shallow convolutional networks with random filters
arXiv preprint arXiv:1606.00021, 2016 (article)
2010
Brendel, Wieland, Thies, Michael
Covariant boost and structure functions of baryons in Gross-Neveu models
Physical Review D, 81(8):085002, APS, 2010 (article)
2009
Brendel, Wieland, Bruckmann, Falk, Janssen, Lukas, Wipf, Andreas, Wozar, Christian
Instanton constituents and fermionic zero modes in twisted CPn models
Physics Letters B, 676(1-3):116-125, Elsevier, 2009 (article)