Jonas Rauber

Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks

arXiv preprint 1903.11359, 2019

Francesco Croce*, Jonas Rauber*, Matthias Hein

@article{croce2019scaling,
  title={Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks},
  author={Francesco Croce and Jonas Rauber and Matthias Hein},
  journal={arXiv preprint arXiv:1903.11359},
  year={2019},
}

arXiv Code

On Evaluating Adversarial Robustness

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},
}

arXiv Code

Towards the first adversarially robust neural network model on MNIST

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},
}

arXiv OpenReview

Generalisation in humans and deep neural networks

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},
}

arXiv Code

Adversarial Vision Challenge

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

Technical Report on the CleverHans v2.1.0 Adversarial Examples Library

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},
}

arXiv Code

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

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},
}

arXiv OpenReview Code

Foolbox: A Python toolbox to benchmark the robustness of machine learning models

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},
}

arXiv Workshop Code

Hi, I'm Jonas!

Publications

Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks

On Evaluating Adversarial Robustness

Towards the first adversarially robust neural network model on MNIST

Generalisation in humans and deep neural networks

Adversarial Vision Challenge

Technical Report on the CleverHans v2.1.0 Adversarial Examples Library

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

Foolbox: A Python toolbox to benchmark the robustness of machine learning models

2019

Apple

ICLR

InterFaces

Bosch Research Foundation Meeting

2018

NeurIPS

DIN Spec Meeting

Intel NIS Workshop

IMPRS-IS Bootcamp

Stuttgart Media University

ICLR

Bosch Research Foundation Meeting

2017

IMPRS-IS Bootcamp

Bernstein Conference

ICML

ETH Learning Systems Summer School

2016

Started my PhD in Machine Learning

Bernstein Conference

MSc in Neural Information Processing