Matthias Bethge

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Alexander S. EckerUniversity of Göttingen, GermanyEmail yang diverifikasi di cs.uni-goettingen.de
Wieland BrendelFellow at ELLIS Institut Tübingen, Group Leader, Max Planck Institute for Intelligent SystemsEmail yang diverifikasi di tuebingen.mpg.de
Leon A. GatysApple Inc.Email yang diverifikasi di bethgelab.org
Andreas ToliasStanford UniversityEmail yang diverifikasi di stanford.edu
Felix WichmannEberhard Karls Universität TübingenEmail yang diverifikasi di uni-tuebingen.de
Matthias KümmererTübingen AI Center, University TuebingenEmail yang diverifikasi di bethgelab.org
Philipp BerensHertie Institute for AI in Brain Health, University of TübingenEmail yang diverifikasi di uni-tuebingen.de
Robert GeirhosResearch Scientist, Google DeepMindEmail yang diverifikasi di google.com
Lucas TheisMabyduckEmail yang diverifikasi di google.com
Claudio MichaelisEllis Institute TübingenEmail yang diverifikasi di tuebingen.mpg.de
Alexander MathisEPFL (Ecole Polytechnique Fédérale de Lausanne / Swiss Federal Institute of Technology)Email yang diverifikasi di epfl.ch
Fabian SinzProfessor for Machine Learning, University GöttingenEmail yang diverifikasi di cs.uni-goettingen.de
Jonas RauberUniversity of Tübingen & Max Planck Research School for Intelligent SystemsEmail yang diverifikasi di uni-tuebingen.de
Mackenzie W. MathisSwiss Federal Institute of Technology in Lausanne (EPFL)Email yang diverifikasi di epfl.ch
Thomas EulerProfessor for Ophthalmic Research, CIN / Centre for Ophthalmology, University of TübingenEmail yang diverifikasi di cin.uni-tuebingen.de
Jakob MackeMachine Learning in Science, Tübingen UniversityEmail yang diverifikasi di uni-tuebingen.de

Ikuti

Matthias Bethge

Tübingen University & Maddox Co-Founder

Email yang diverifikasi di bethgelab.org - Beranda

Computational Neuroscience Machine Learning Vision


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Image style transfer using convolutional neural networks LA Gatys, AS Ecker, M Bethge Proceedings of the IEEE conference on computer vision and pattern …, 2016	6988	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	4281	2018
A neural algorithm of artistic style LA Gatys arXiv preprint arXiv:1508.06576, 2015	3724	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	3289	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	2236	2020
Texture synthesis using convolutional neural networks L Gatys, AS Ecker, M Bethge Advances in Neural Information Processing Systems, 262-270, 2015	1835	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	1690	2017
A note on the evaluation of generative models L Theis, A Oord, M Bethge arXiv preprint arXiv:1511.01844, 2015	1366	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	1266	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	1037	2016
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	777	2018
Foolbox: A python toolbox to benchmark the robustness of machine learning models J Rauber, W Brendel, M Bethge arXiv preprint arXiv:1707.04131, 2017	732	2017
Decorrelated neuronal firing in cortical microcircuits AS Ecker, P Berens, GA Keliris, M Bethge, NK Logothetis, AS Tolias science 327 (5965), 584-587, 2010	731	2010
Approximating cnns with bag-of-local-features models works surprisingly well on imagenet W Brendel, M Bethge arXiv preprint arXiv:1904.00760, 2019	726	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	580	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	575	2017
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	536	2019
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	533	2020
Deep gaze i: Boosting saliency prediction with feature maps trained on imagenet M Kümmerer, L Theis, M Bethge arXiv preprint arXiv:1411.1045, 2014	522	2014
Towards the first adversarially robust neural network model on MNIST L Schott, J Rauber, M Bethge, W Brendel arXiv preprint arXiv:1805.09190, 2018	462	2018

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