Follow
Wieland Brendel
Wieland Brendel
Research Group Leader, Max Planck Institute for Intelligent Systems
Verified email at tuebingen.mpg.de - Homepage
Title
Cited by
Cited by
Year
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
R Geirhos, P Rubisch, C Michaelis, M Bethge, FA Wichmann, W Brendel
Seventh International Conference on Learning Representations (ICLR 2019), 2018
18222018
Decision-based adversarial attacks: Reliable attacks against black-box machine learning models
W Brendel, J Rauber, M Bethge
Sixth International Conference on Learning Representations (ICLR 2018), 2017
10102017
Shortcut Learning in Deep Neural Networks
R Geirhos, JH Jacobsen, C Michaelis, R Zemel, W Brendel, M Bethge, ...
Nature Machine Intelligence volume 2, pages665–673(2020), 2020
8152020
On evaluating adversarial robustness
N Carlini, A Athalye, N Papernot, W Brendel, J Rauber, D Tsipras, ...
arXiv preprint arXiv:1902.06705, 2019
6582019
Foolbox v0. 8.0: A python toolbox to benchmark the robustness of machine learning models
J Rauber, W Brendel, M Bethge
Reliable Machine Learning in the Wild Workshop, 34th International …, 2017
549*2017
On adaptive attacks to adversarial example defenses
F Tramer, N Carlini, W Brendel, A Madry
34th Conference on Neural Information Processing Systems (NeurIPS), 2020
5182020
Approximating cnns with bag-of-local-features models works surprisingly well on imagenet
W Brendel, M Bethge
Seventh International Conference on Learning Representations (ICLR 2019), 2019
4612019
Demixed principal component analysis of neural population data
D Kobak, W Brendel, C Constantinidis, CE Feierstein, A Kepecs, ...
elife 5, e10989, 2016
3892016
Towards the first adversarially robust neural network model on MNIST
L Schott, J Rauber, M Bethge, W Brendel
Seventh International Conference on Learning Representations (ICLR 2019), 2018
3222018
Benchmarking robustness in object detection: Autonomous driving when winter is coming
C Michaelis, B Mitzkus, R Geirhos, E Rusak, O Bringmann, AS Ecker, ...
NeurIPS 2019 Workshop on Machine Learning for Autonomous Driving, 2019
2212019
Improving robustness against common corruptions by covariate shift adaptation
S Schneider, E Rusak, L Eck, O Bringmann, W Brendel, M Bethge
34th Conference on Neural Information Processing Systems (NeurIPS), 2020
1652020
A simple way to make neural networks robust against diverse image corruptions
E Rusak, L Schott, RS Zimmermann, J Bitterwolf, O Bringmann, M Bethge, ...
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
1232020
Foolbox native: Fast adversarial attacks to benchmark the robustness of machine learning models in pytorch, tensorflow, and jax
J Rauber, R Zimmermann, M Bethge, W Brendel
Journal of Open Source Software 5 (53), 2607, 2020
1142020
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
J von Kügelgen, Y Sharma, L Gresele, W Brendel, B Schölkopf, ...
35th Conference on Neural Information Processing Systems (NeurIPS), 2021
932021
Contrastive Learning Inverts the Data Generating Process
RS Zimmermann, Y Sharma, S Schneider, M Bethge, W Brendel
International Conference on Machine Learning (ICML 2021), 2021
812021
Five points to check when comparing visual perception in humans and machines
CM Funke, J Borowski, K Stosio, W Brendel, TSA Wallis, M Bethge
Journal of Vision 21 (3), 16-16, 2021
80*2021
Accurate, reliable and fast robustness evaluation
W Brendel, J Rauber, M Kümmerer, I Ustyuzhaninov, M Bethge
33rd Conference on Neural Information Processing Systems (NeurIPS), 12841-12851, 2019
792019
Instanton constituents and fermionic zero modes in twisted CPn models
W Brendel, F Bruckmann, L Janssen, A Wipf, C Wozar
Physics Letters B 676 (1-3), 116-125, 2009
712009
Demixed principal component analysis
W Brendel, R Romo, CK Machens
Advances in Neural Information Processing Systems 24 (NIPS 2011), 2654-2662, 2011
612011
Partial success in closing the gap between human and machine vision
R Geirhos, K Narayanappa, B Mitzkus, T Thieringer, M Bethge, ...
35th Conference on Neural Information Processing Systems (NeurIPS), 2021
572021
The system can't perform the operation now. Try again later.
Articles 1–20