tag:joss.theoj.org,2005:/papers/by/Matthias%20BethgeJournal of Open Source Software2020-09-27T10:49:02ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/19372020-09-27T10:49:02Z2021-02-15T11:30:09ZFoolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAXacceptedv3.1.02020-08-10 18:30:38 UTC532020-09-27 10:49:02 UTC520202607JonasRauberTübingen AI Center, University of Tübingen, Germany, International Max Planck Research School for Intelligent Systems, Tübingen, Germany0000-0001-6795-9441RolandZimmermannTübingen AI Center, University of Tübingen, Germany, International Max Planck Research School for Intelligent Systems, Tübingen, GermanyMatthiasBethgeTübingen AI Center, University of Tübingen, Germany, Bernstein Center for Computational Neuroscience Tübingen, GermanyWielandBrendelTübingen AI Center, University of Tübingen, Germany, Bernstein Center for Computational Neuroscience Tübingen, Germany10.21105/joss.02607https://doi.org/10.5281/zenodo.4050932Python, JavaScript, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.02607.pdfpython, machine learning, adversarial attacks, neural networks, pytorch, tensorflow, jax, keras, eagerpy