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EagerPy: Writing Code That Works Natively with PyTorch, TensorFlow, JAX, and NumPy
EagerPy is a Python framework that lets you write code that automaticall...
08/10/2020 ∙ by Jonas Rauber, et al. ∙
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Fast Differentiable Clipping-Aware Normalization and Rescaling
Rescaling a vector δ⃗∈ℝ^n to a desired length is a common operation in m...
07/15/2020 ∙ by Jonas Rauber, et al. ∙
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Modeling patterns of smartphone usage and their relationship to cognitive health
The ubiquity of smartphone usage in many people's lives make it a rich s...
11/13/2019 ∙ by Jonas Rauber, et al. ∙
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Accurate, reliable and fast robustness evaluation
Throughout the past five years, the susceptibility of neural networks to...
07/01/2019 ∙ by Wieland Brendel, et al. ∙
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Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks
Modern neural networks are highly non-robust against adversarial manipul...
03/27/2019 ∙ by Francesco Croce, et al. ∙
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On Evaluating Adversarial Robustness
Correctly evaluating defenses against adversarial examples has proven to...
02/18/2019 ∙ by Nicholas Carlini, et al. ∙
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Generalisation in humans and deep neural networks
We compare the robustness of humans and current convolutional deep neura...
08/27/2018 ∙ by Robert Geirhos, et al. ∙
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Adversarial Vision Challenge
The NIPS 2018 Adversarial Vision Challenge is a competition to facilitat...
08/06/2018 ∙ by Wieland Brendel, et al. ∙
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Robust Perception through Analysis by Synthesis
The intriguing susceptibility of deep neural networks to minimal input p...
05/23/2018 ∙ by Lukas Schott, et al. ∙
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Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models
Many machine learning algorithms are vulnerable to almost imperceptible ...
12/12/2017 ∙ by Wieland Brendel, et al. ∙
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Foolbox v0.8.0: A Python toolbox to benchmark the robustness of machine learning models
Even todays most advanced machine learning models are easily fooled by a...
07/13/2017 ∙ by Jonas Rauber, et al. ∙
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Comparing deep neural networks against humans: object recognition when the signal gets weaker
Human visual object recognition is typically rapid and seemingly effortl...
06/21/2017 ∙ by Robert Geirhos, et al. ∙
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