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ORCIDWieland Brendel
- > Home > Persons > Wieland Brendel
Publications
- 2024
[c30]Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel:
Does CLIP's generalization performance mainly stem from high train-test similarity? ICLR 2024- [c29]Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel:
Provable Compositional Generalization for Object-Centric Learning. ICLR 2024 - 2023
- [j7]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) - [j6]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) - [c24]Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel:
Compositional Generalization from First Principles. NeurIPS 2023 - [d3]Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel:
nl-causal-representations. Version v1.0.1. Zenodo, 2023 [all versions]
- [i37]Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel:
Compositional Generalization from First Principles. CoRR abs/2307.05596 (2023) - [i36]Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel:
Provable Compositional Generalization for Object-Centric Learning. CoRR abs/2310.05327 (2023) - [i35]Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel:
Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity? CoRR abs/2310.09562 (2023) - 2022
- [j5]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) - [c22]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 - [d1]Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel:
nl-causal-representations. Version 1.0.0. Zenodo, 2022 [all versions] - 2021
- [j4]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: 183:1-183:61 (2021) - [c19]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 - [c18]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 - [c17]Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel:
Contrastive Learning Inverts the Data Generating Process. ICML 2021: 12979-12990 - [c16]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: 11730-11744 - [c13]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: 23885-23899 - [i31]Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel:
Contrastive Learning Inverts the Data Generating Process. CoRR abs/2102.08850 (2021) - [i29]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 abs/2104.12928 (2021) - [i27]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 abs/2106.07411 (2021) - [i26]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 abs/2106.12447 (2021) - [i25]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 abs/2107.08221 (2021) - 2020
- [j3]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): 2607 (2020) - [j2]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): 665-673 (2020) - [c12]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: 53-69 - [c11]Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge:
Improving robustness against common corruptions by covariate shift adaptation. NeurIPS 2020 - [i24]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 abs/2001.06057 (2020) - [i22]Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard S. Zemel, Wieland Brendel, Matthias Bethge, Felix A. Wichmann:
Shortcut Learning in Deep Neural Networks. CoRR abs/2004.07780 (2020) - [i21]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 abs/2004.09406 (2020) - [i20]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 abs/2006.07034 (2020) - [i19]Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge:
Improving robustness against common corruptions by covariate shift adaptation. CoRR abs/2006.16971 (2020) - [i18]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. CoRR abs/2007.10930 (2020) - [i17]Jonas Rauber, Matthias Bethge, Wieland Brendel:
EagerPy: Writing Code That Works Natively with PyTorch, TensorFlow, JAX, and NumPy. CoRR abs/2008.04175 (2020) - [i16]Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Matthias Bethge, Felix A. Wichmann, Wieland Brendel:
On the surprising similarities between supervised and self-supervised models. CoRR abs/2010.08377 (2020) - [i15]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 abs/2010.12606 (2020) - 2019
- [c9]Wieland Brendel, Matthias Bethge:
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet. ICLR (Poster) 2019 - [c8]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 - [c7]Lukas Schott, Jonas Rauber, Matthias Bethge, Wieland Brendel:
Towards the first adversarially robust neural network model on MNIST. ICLR (Poster) 2019 - [c6]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: 9525-9535 - [c5]Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge:
Accurate, reliable and fast robustness evaluation. NeurIPS 2019: 12841-12851 - [i13]Wieland Brendel, Matthias Bethge:
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet. CoRR abs/1904.00760 (2019) - [i12]Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge:
Accurate, reliable and fast robustness evaluation. CoRR abs/1907.01003 (2019) - [i11]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 abs/1907.07484 (2019) - [i10]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 abs/1911.05072 (2019) - 2018
- [c4]Wieland Brendel, Jonas Rauber, Matthias Bethge:
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models. ICLR (Poster) 2018 - [i9]Alexander Böttcher, Wieland Brendel, Bernhard Englitz, Matthias Bethge:
Trace your sources in large-scale data: one ring to find them all. CoRR abs/1803.08882 (2018) - [i8]Lukas Schott, Jonas Rauber, Wieland Brendel, Matthias Bethge:
Robust Perception through Analysis by Synthesis. CoRR abs/1805.09190 (2018) - [i7]Ivan Ustyuzhaninov, Claudio Michaelis, Wieland Brendel, Matthias Bethge:
One-shot Texture Segmentation. CoRR abs/1807.02654 (2018) - [i6]Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge:
Adversarial Vision Challenge. CoRR abs/1808.01976 (2018) - [i5]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 abs/1811.12231 (2018) - 2017
- [c3]Ivan Ustyuzhaninov, Wieland Brendel, Leon A. Gatys, Matthias Bethge:
What does it take to generate natural textures? ICLR (Poster) 2017 - [i4]Wieland Brendel, Matthias Bethge:
Comment on "Biologically inspired protection of deep networks from adversarial attacks". CoRR abs/1704.01547 (2017) - [i3]Jonas Rauber, Wieland Brendel, Matthias Bethge:
Foolbox v0.8.0: A Python toolbox to benchmark the robustness of machine learning models. CoRR abs/1707.04131 (2017) - [i2]Wieland Brendel, Jonas Rauber, Matthias Bethge:
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models. CoRR abs/1712.04248 (2017) - 2016
- [i1]Ivan Ustyuzhaninov, Wieland Brendel, Leon A. Gatys, Matthias Bethge:
Texture Synthesis Using Shallow Convolutional Networks with Random Filters. CoRR abs/1606.00021 (2016)
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last updated on 2024-09-13 01:41 CEST by the dblp team
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