Matthias Bethge

Citado por

	Todos	Desde 2019
Citações	43726	36634
Índice h	74	62
Índice i10	135	128

8000

4000

2000

6000

201020112012201320142015201620172018201920202021202220232024139 202 215 321 320 473 830 1603 2384 3634 4781 6375 6993 7511 7261

Acesso público

Ver tudo

88 artigos

1 artigo

disponível

não disponível

Com base em autorizações de financiamento

Coautores

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

Seguir

Matthias Bethge

Tübingen University & Maddox Co-Founder

Email confirmado em bethgelab.org - Página inicial

Computational Neuroscience Machine Learning Vision


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Image style transfer using convolutional neural networks LA Gatys, AS Ecker, M Bethge Proceedings of the IEEE conference on computer vision and pattern …, 2016	6756	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	4027	2018
A neural algorithm of artistic style LA Gatys arXiv preprint arXiv:1508.06576, 2015	3646	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	3190	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	2099	2020
Texture synthesis using convolutional neural networks L Gatys, AS Ecker, M Bethge Advances in Neural Information Processing Systems, 262-270, 2015	1801	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	1630	2017
A note on the evaluation of generative models L Theis, A Oord, M Bethge arXiv preprint arXiv:1511.01844, 2015	1340	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	1198	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	999	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	746	2018
Decorrelated neuronal firing in cortical microcircuits AS Ecker, P Berens, GA Keliris, M Bethge, NK Logothetis, AS Tolias science 327 (5965), 584-587, 2010	729	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	718	2017
Approximating cnns with bag-of-local-features models works surprisingly well on imagenet W Brendel, M Bethge arXiv preprint arXiv:1904.00760, 2019	705	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	567	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	565	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	514	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	505	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	501	2020
Towards the first adversarially robust neural network model on MNIST L Schott, J Rauber, M Bethge, W Brendel arXiv preprint arXiv:1805.09190, 2018	452	2018

O sistema não pode efectuar a operação agora. Tente mais tarde.

Artigos 1–20

Citações por ano

Citações duplicadas

Citações unidas

Adicionar coautoresCoautores

Seguir

Citado por

Coautores