Philip Sperl

CoRR, 2023

Shortcut Detection with Variational Autoencoders.

[BibT_eX]

[DOI]

CoRR, 2023

Protecting Publicly Available Data With Machine Learning Shortcuts.

[BibT_eX]

[DOI]

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

Visualizing Automatic Speech Recognition - Means for a Better Understanding?

[BibT_eX]

[DOI]

CoRR, 2022

R2-AD2: Detecting Anomalies by Analysing the Raw Gradient.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Double-Adversarial Activation Anomaly Detection: Adversarial Autoencoders are Anomaly Generators.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2022

Anomaly Detection by Recombining Gated Unsupervised Experts.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2022

Assessing the Impact of Transformations on Physical Adversarial Attacks.

[BibT_eX]

[DOI]

Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security, 2022

2021

Gradient Masking and the Underestimated Robustness Threats of Differential Privacy in Deep Learning.

[BibT_eX]

[DOI]

Franziska Boenisch

CoRR, 2021

DA3G: Detecting Adversarial Attacks by Analysing Gradients.

[BibT_eX]

[DOI]

Proceedings of the Computer Security - ESORICS 2021, 2021

2020

Optimizing Information Loss Towards Robust Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

A<sup>3</sup>: Activation Anomaly Analysis.

[BibT_eX]

[DOI]

CoRR, 2020

Activation Anomaly Analysis.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

DLA: Dense-Layer-Analysis for Adversarial Example Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE European Symposium on Security and Privacy, 2020

2019

DLA: Dense-Layer-Analysis for Adversarial Example Detection.

[BibT_eX]

[DOI]

CoRR, 2019

Side-Channel Aware Fuzzing.

[BibT_eX]

[DOI]