Matthias Bethge
Matthias Bethge
Tübingen University & Maddox Co-Founder
Verified email at - Homepage
Cited by
Cited by
Image style transfer using convolutional neural networks
LA Gatys, AS Ecker, M Bethge
Proceedings of the IEEE conference on computer vision and pattern …, 2016
DeepLabCut: markerless pose estimation of user-defined body parts with deep learning
A Mathis, P Mamidanna, KM Cury, T Abe, VN Murthy, MW Mathis, ...
Nature neuroscience 21 (9), 1281-1289, 2018
A neural algorithm of artistic style
LA Gatys, AS Ecker, M Bethge
arXiv preprint arXiv:1508.06576, 2015
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
arXiv preprint arXiv:1811.12231, 2018
Shortcut learning in deep neural networks
R Geirhos, JH Jacobsen, C Michaelis, R Zemel, W Brendel, M Bethge, ...
Nature Machine Intelligence 2 (11), 665-673, 2020
Texture synthesis using convolutional neural networks
L Gatys, AS Ecker, M Bethge
Advances in Neural Information Processing Systems, 262-270, 2015
Decision-based adversarial attacks: Reliable attacks against black-box machine learning models
W Brendel, J Rauber, M Bethge
arXiv preprint arXiv:1712.04248, 2017
A note on the evaluation of generative models
L Theis, A Oord, M Bethge
arXiv preprint arXiv:1511.01844, 2015
Using DeepLabCut for 3D markerless pose estimation across species and behaviors
T Nath, A Mathis, AC Chen, A Patel, M Bethge, MW Mathis
Nature protocols 14 (7), 2152-2176, 2019
The functional diversity of retinal ganglion cells in the mouse
T Baden, P Berens, K Franke, M Román Rosón, M Bethge, T Euler
Nature 529 (7586), 345-350, 2016
Decorrelated neuronal firing in cortical microcircuits
AS Ecker, P Berens, GA Keliris, M Bethge, NK Logothetis, AS Tolias
science 327 (5965), 584-587, 2010
Foolbox: A python toolbox to benchmark the robustness of machine learning models
J Rauber, W Brendel, M Bethge
arXiv preprint arXiv:1707.04131, 2017
Generalisation in humans and deep neural networks
R Geirhos, CRM Temme, J Rauber, HH Schütt, M Bethge, FA Wichmann
Advances in neural information processing systems 31, 2018
Approximating cnns with bag-of-local-features models works surprisingly well on imagenet
W Brendel, M Bethge
arXiv preprint arXiv:1904.00760, 2019
Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq
CR Cadwell, A Palasantza, X Jiang, P Berens, Q Deng, M Yilmaz, ...
Nature biotechnology 34 (2), 199-203, 2016
Controlling perceptual factors in neural style transfer
LA Gatys, AS Ecker, M Bethge, A Hertzmann, E Shechtman
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Deep gaze i: Boosting saliency prediction with feature maps trained on imagenet
M Kümmerer, L Theis, M Bethge
arXiv preprint arXiv:1411.1045, 2014
Benchmarking robustness in object detection: Autonomous driving when winter is coming
C Michaelis, B Mitzkus, R Geirhos, E Rusak, O Bringmann, AS Ecker, ...
arXiv preprint arXiv:1907.07484, 2019
Towards the first adversarially robust neural network model on MNIST
L Schott, J Rauber, M Bethge, W Brendel
arXiv preprint arXiv:1805.09190, 2018
Improving robustness against common corruptions by covariate shift adaptation
S Schneider, E Rusak, L Eck, O Bringmann, W Brendel, M Bethge
Advances in Neural Information Processing Systems 33, 2020
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