33 citations · 47 across the 5 of their papers we have counts for
6 papers
Robustness testing of AI systems: A case study for traffic sign recognition
Christian Berghoff, Pavol Bielik, Matthias Neu +2
In the last years, AI systems, in particular neural networks, have seen a tremendous increase in performance, and they are now used in a broad range of applications. Unlike classic…
Automated Discovery of Adaptive Attacks on Adversarial Defenses
Chengyuan Yao, Pavol Bielik, Petar Tsankov +1
Reliable evaluation of adversarial defenses is a challenging task, currently limited to an expert who manually crafts attacks that exploit the defense's inner workings or approache…
Adversarial Attacks on Probabilistic Autoregressive Forecasting Models
Raphaël Dang-Nhu, Gagandeep Singh, Pavol Bielik +1
We develop an effective generation of adversarial attacks on neural models that output a sequence of probability distributions rather than a sequence of single values. This setting…
Adversarial Robustness for Code
Pavol Bielik, Martin Vechev
Machine learning and deep learning in particular has been recently used to successfully address many tasks in the domain of code such as finding and fixing bugs, code completion, d…
Learning to Infer User Interface Attributes from Images
Philippe Schlattner, Pavol Bielik, Martin Vechev
We explore a new domain of learning to infer user interface attributes that helps developers automate the process of user interface implementation. Concretely, given an input image…
Learning a Static Analyzer from Data
Pavol Bielik, Veselin Raychev, Martin Vechev
To be practically useful, modern static analyzers must precisely model the effect of both, statements in the programming language as well as frameworks used by the program under an…