( en | de | ru )

 

Disambiguation of "Rauber, Jonas"

Author of the publication

copydeleteadd this publication to your clipboard
On Evaluating Adversarial Robustness.

, , , , , , , , and . CoRR, (2019)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Herbert Räuber

Martin Rauber

Klaus Rauber

Lucio Rauber

Andreas Räuber

 

Other publications of authors with the same name

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models., , and . CoRR, (2017)EagerPy: Writing Code That Works Natively with PyTorch, TensorFlow, JAX, and NumPy., , and . CoRR, (2020)Fast Differentiable Clipping-Aware Normalization and Rescaling., and . CoRR, (2020)Towards the first adversarially robust neural network model on MNIST., , , and . ICLR (Poster), OpenReview.net, (2019)Foolbox: A Python toolbox to benchmark the robustness of machine learning models, , and . (2017)cite arxiv:1707.04131Comment: Code and examples available at https://github.com/bethgelab/foolbox and documentation available at http://foolbox.readthedocs.io.Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks., , and . CoRR, (2019)On Evaluating Adversarial Robustness., , , , , , , , and . CoRR, (2019)Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX., , , and . J. Open Source Softw., 5 (53): 2607 (2020)Adversarial Vision Challenge., , , , , , , and . CoRR, (2018)Scaling up the Randomized Gradient-Free Adversarial Attack Reveals Overestimation of Robustness Using Established Attacks., , and . Int. J. Comput. Vis., 128 (4): 1028-1046 (2020)