Zimmermann, Roland S, Brendel, Wieland, Tramer, Florian, Carlini, Nicholas Increasing Confidence in Adversarial Robustness Evaluations arXiv preprint arXiv:2206.13991, 2022 (article)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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Oladazimi, Maysam, Brendel, Wieland, Schwarz, Cornelius Biomechanical texture coding in rat whiskers Scientific reports, 8(1):1-12, Nature Publishing Group, 2018 (article)

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Ustyuzhaninov, Ivan, Michaelis, Claudio, Brendel, Wieland, Bethge, Matthias One-shot texture segmentation arXiv preprint arXiv:1807.02654, 2018 (article)

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Brendel, Wieland, Bethge, Matthias Comment on" Biologically inspired protection of deep networks from adversarial attacks" arXiv preprint arXiv:1704.01547, 2017 (article)

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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)

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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)

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Brendel, Wieland, Thies, Michael Covariant boost and structure functions of baryons in Gross-Neveu models Physical Review D, 81(8):085002, APS, 2010 (article)

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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)

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