579 citations · 591 across the 4 of their papers we have counts for
6 papers · 1 filter
EagerPy: Writing Code That Works Natively with PyTorch, TensorFlow, JAX, and NumPy
Jonas Rauber, Matthias Bethge, Wieland Brendel
EagerPy is a Python framework that lets you write code that automatically works natively with PyTorch, TensorFlow, JAX, and NumPy. Library developers no longer need to choose betwe…
Fast Differentiable Clipping-Aware Normalization and Rescaling
Jonas Rauber, Matthias Bethge
Rescaling a vector to a desired length is a common operation in many areas such as data science and machine learning. When the rescaled perturbation $η\vec…
Modeling patterns of smartphone usage and their relationship to cognitive health
Jonas Rauber, Emily B. Fox, Leon A. Gatys
The ubiquity of smartphone usage in many people's lives make it a rich source of information about a person's mental and cognitive state. In this work we analyze 12 weeks of phone…
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks
Francesco Croce, Jonas Rauber, Matthias Hein
Modern neural networks are highly non-robust against adversarial manipulation. A significant amount of work has been invested in techniques to compute lower bounds on robustness th…
On Evaluating Adversarial Robustness
Nicholas Carlini, Anish Athalye, Nicolas Papernot +6
Correctly evaluating defenses against adversarial examples has proven to be extremely difficult. Despite the significant amount of recent work attempting to design defenses that wi…
Adversarial Vision Challenge
Wieland Brendel, Jonas Rauber, Alexey Kurakin +5
The NIPS 2018 Adversarial Vision Challenge is a competition to facilitate measurable progress towards robust machine vision models and more generally applicable adversarial attacks…