Jonas Rauber - RankMe

19 papers A* 2Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2021	—	`—`	Advances in Reliably Evaluating and Improving Adversarial Robustness. Jonas Rauber
2020	J	`jnl`	EagerPy: Writing Code That Works Natively with PyTorch, TensorFlow, JAX, and NumPy. CoRR Jonas Rauber, Matthias Bethge, Wieland Brendel
2020	J	`jnl`	Fast Differentiable Clipping-Aware Normalization and Rescaling. CoRR Jonas Rauber, Matthias Bethge
2020	J	`jnl`	Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX. J. Open Source Softw. Jonas Rauber, Roland Zimmermann, Matthias Bethge, Wieland Brendel
2020	J	`jnl`	Scaling up the Randomized Gradient-Free Adversarial Attack Reveals Overestimation of Robustness Using Established Attacks. Int. J. Comput. Vis. Francesco Croce, Jonas Rauber, Matthias Hein
2019	A*	`conf`	Accurate, reliable and fast robustness evaluation. NeurIPS Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge
2019	J	`jnl`	Accurate, reliable and fast robustness evaluation. CoRR Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge
2019	J	`jnl`	Modeling patterns of smartphone usage and their relationship to cognitive health. CoRR Jonas Rauber, Emily B. Fox, Leon A. Gatys
2019	J	`jnl`	On Evaluating Adversarial Robustness. CoRR Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian J. Goodfellow, Aleksander Madry, Alexey Kurakin
2019	J	`jnl`	Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks. CoRR Francesco Croce, Jonas Rauber, Matthias Hein
2019	—	`conf`	Towards the first adversarially robust neural network model on MNIST. ICLR (Poster) Lukas Schott, Jonas Rauber, Matthias Bethge, Wieland Brendel
2018	J	`jnl`	Adversarial Vision Challenge. CoRR Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge
2018	—	`conf`	Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models. ICLR (Poster) Wieland Brendel, Jonas Rauber, Matthias Bethge
2018	A*	`conf`	Generalisation in humans and deep neural networks. NeurIPS Robert Geirhos, Carlos R. Medina Temme, Jonas Rauber, Heiko H. Schütt, Matthias Bethge, Felix A. Wichmann
2018	J	`jnl`	Generalisation in humans and deep neural networks. CoRR Robert Geirhos, Carlos R. Medina Temme, Jonas Rauber, Heiko H. Schütt, Matthias Bethge, Felix A. Wichmann
2018	J	`jnl`	Robust Perception through Analysis by Synthesis. CoRR Lukas Schott, Jonas Rauber, Wieland Brendel, Matthias Bethge
2017	J	`jnl`	Comparing deep neural networks against humans: object recognition when the signal gets weaker. CoRR Robert Geirhos, David H. J. Janssen, Heiko H. Schütt, Jonas Rauber, Matthias Bethge, Felix A. Wichmann
2017	J	`jnl`	Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models. CoRR Wieland Brendel, Jonas Rauber, Matthias Bethge
2017	J	`jnl`	Foolbox v0.8.0: A Python toolbox to benchmark the robustness of machine learning models. CoRR Jonas Rauber, Wieland Brendel, Matthias Bethge