I am a PhD student at the Max Planck Research School for Intelligent Systems in Tübingen, working in the lab of Matthias Bethge. My goal is to build more intelligent machines that improve our lives, and doing so by taking inspiration from humans. My current research focuses on understanding and improving the robustness of deep neural networks.
Machine Learning for Health Workshop, 33rd Conference on Neural Information Processing Systems, 2019
Jonas Rauber, Emily Fox, Leon Gatys
@inproceedings{rauber2019modeling,
title={Modeling patterns of smartphone usage and their relationship to cognitive health},
author={Jonas Rauber and Emily Fox and Leon Gatys},
booktitle={Machine Learning for Health Workshop, 33rd Conference on Neural Information Processing Systems},
year={2019},
}To appear in Advances in Neural Information Processing Systems 32, 2019
Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge
@inproceedings{brendel2019accurate,
title={Accurate, reliable and fast robustness evaluation},
author={Wieland Brendel and Jonas Rauber and Matthias K{\"u}mmerer and Ivan Ustyuzhaninov and Matthias Bethge},
booktitle={Advances in Neural Information Processing Systems 32},
year={2019},
}International Journal of Computer Vision
Francesco Croce*, Jonas Rauber*, Matthias Hein
@article{croce2019scaling,
author="Croce, Francesco
and Rauber, Jonas
and Hein, Matthias",
title="Scaling up the Randomized Gradient-Free Adversarial Attack Reveals Overestimation of Robustness Using Established Attacks",
journal="International Journal of Computer Vision",
year="2019",
month="Oct",
day="03",
issn="1573-1405",
doi="10.1007/s11263-019-01213-0",
url="https://doi.org/10.1007/s11263-019-01213-0"
}arXiv preprint 1902.06705, 2019
Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian Goodfellow, Aleksander Madry, Alexey Kurakin
@article{carlini2019evaluating,
title={On Evaluating Adversarial Robustness},
author={Nicholas Carlini and Anish Athalye and Nicolas Papernot and Wieland Brendel and Jonas Rauber and Dimitris Tsipras and Ian Goodfellow and Aleksander Madry and Alexey Kurakin},
journal={arXiv preprint arXiv:1902.06705},
year={2019},
}International Conference on Learning Representations, 2019
Lukas Schott*, Jonas Rauber*, Matthias Bethge, Wieland Brendel
@inproceedings{schott2018towards,
title={Towards the first adversarially robust neural network model on {MNIST}},
author={Lukas Schott and Jonas Rauber and Matthias Bethge and Wieland Brendel},
booktitle={International Conference on Learning Representations},
year={2019},
url={https://openreview.net/forum?id=S1EHOsC9tX},
}Advances in Neural Information Processing Systems 31, 2018
Robert Geirhos*, Carlos R. Medina Temme*, Jonas Rauber*, Heiko H. Schuett, Matthias Bethge, Felix A. Wichmann
@incollection{geirhos2018generalisation,
title={Generalisation in humans and deep neural networks},
author={Geirhos, Robert and Temme, Carlos R Medina and Rauber, Jonas and Schuett, Heiko H and Bethge, Matthias and Wichmann, Felix A},
booktitle={Advances in Neural Information Processing Systems 31},
year={2018},
}Competition Track of the 32nd Conference on Neural Information Processing Systems, 2018
Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge
@article{brendel2018adversarial,
title={Adversarial Vision Challenge},
author={Brendel, Wieland and Rauber, Jonas and Kurakin, Alexey and Papernot, Nicolas and Veliqi, Behar and Salath{\'e}, Marcel and Mohanty, Sharada P and Bethge, Matthias},
journal={arXiv preprint arXiv:1808.01976},
year={2018}
}arXiv Competition Track crowdAI
arXiv preprint 1610.00768, 2018
Nicolas Papernot, Fartash Faghri, Nicholas Carlini, Ian Goodfellow, Reuben Feinman, Alexey Kurakin, Cihang Xie, Yash Sharma, Tom Brown, Aurko Roy, Alexander Matyasko, Vahid Behzadan, Karen Hambardzumyan, Zhishuai Zhang, Yi-Lin Juang, Zhi Li, Ryan Sheatsley, Abhibhav Garg, Jonathan Uesato, Willi Gierke, Yinpeng Dong, David Berthelot, Paul Hendricks, Jonas Rauber, Rujun Long, Patrick McDaniel
@techreport{papernot2016technical,
title={Technical report on the cleverhans {v2.1.0} adversarial examples library},
author={Nicolas Papernot, Fartash Faghri, Nicholas Carlini, Ian Goodfellow, Reuben Feinman, Alexey Kurakin, Cihang Xie, Yash Sharma, Tom Brown, Aurko Roy, Alexander Matyasko, Vahid Behzadan, Karen Hambardzumyan, Zhishuai Zhang, Yi-Lin Juang, Zhi Li, Ryan Sheatsley, Abhibhav Garg, Jonathan Uesato, Willi Gierke, Yinpeng Dong, David Berthelot, Paul Hendricks, Jonas Rauber, Rujun Long, Patrick McDaniel},
year={2018},
url={https://arxiv.org/abs/1610.00768},
}International Conference on Learning Representations, 2018
Wieland Brendel*, Jonas Rauber*, Matthias Bethge
@inproceedings{brendel2018decisionbased,
title={Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models},
author={Wieland Brendel and Jonas Rauber and Matthias Bethge},
booktitle={International Conference on Learning Representations},
year={2018},
url={https://openreview.net/forum?id=SyZI0GWCZ},
}Reliable Machine Learning in the Wild Workshop, 34th International Conference on Machine Learning, 2017
Jonas Rauber*, Wieland Brendel*, Matthias Bethge
@inproceedings{rauber2017foolbox,
title={Foolbox: A Python toolbox to benchmark the robustness of machine learning models},
author={Rauber, Jonas and Brendel, Wieland and Bethge, Matthias},
booktitle={Reliable Machine Learning in the Wild Workshop, 34th International Conference on Machine Learning},
year={2017},
url={http://arxiv.org/abs/1707.04131},
}Bremen, Germany
I will teach a course on How to evaluate adversarial robustness at the Autumn School on Deep Learning and Inverse Problems at the University of Bremen.
Seattle, USA
Starting end of May, I will be joining Apple's machine learning group in Seattle to do a four-month internship.
New Orleans, USA
I will be attending this years International Conference on Learning Representations in New Orleans.
Potsdam, Germany
April 2019
Stuttgart, Germany
Februar 2019
Montreal, Canada
Thirty-Second Conference on Neural Information Processing Systems, December 2018
Berlin, Germany
October 2018
Munich, Germany
September 2018
Germany
Yearly meeting of the International Max Planck Research School, July 2018
Stuttgart, Germany
Workshop to prepare the launch of the Bundeswettbewerb für Künstliche Intelligenz, July 2018
Vancouver, Germany
International Conference on Learning Representations, April 2018
Stuttgart, Germany
Februar 2018
Baden-Württemberg, Germany
Yearly meeting of the International Max Planck Research School, October 2017
Göttingen, Germany
September 2017
Sydney, Australia
International Conference on Machine Learning, August 2017
Zurich, Switzerland
July 2017
Tübingen, Germany
In November 2016, I started my PhD in the Bethge lab at University of Tübingen and the International Max Planck Research School for Intelligent Systems.
Berlin, Germany
September 2016
Tübingen, Germany
In July 2016, I graduated from the University of Tübingen as a Master of Science in Neural Information Processing.