Publications associées à A geometry-inspired decision-based attack

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Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Sabine Süsstrunk, Mathieu Salzmann, Yulun Jiang, Chen Liu, Zhuoyi Huang

We address the problem of stably and efficiently training a deep neural network robust to adversarial perturbations bounded by an

l_1

norm. We demonstrate that achieving robustness against

l_1

-bounded perturbations is more challenging than in the

l_2

...

2023

A geometry-inspired decision-based attack

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Sparse Attacks for Manipulating Explanations in Deep Neural Network Models

Predicting nonlinear optical scattering with physics-driven neural networks

Unconstrained Parametrization of Dissipative and Contracting Neural Ordinary Differential Equations

Layer-Wise Learning Framework for Efficient DNN Deployment in Biomedical Wearable Systems

Exploring neural networks and their potential for species distribution modeling

From Prediction to Prevention: Leveraging Deep Learning in Traffic Accident Prediction Systems

DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications

Hardware-Software Co-design for Improved Resource Utilization in DNN Accelerators

Improved calorimetric particle identification in NA62 using machine learning techniques

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Layer-Wise Learning Framework for Efficient DNN Deployment in Biomedical Wearable Systems

Unconstrained Parametrization of Dissipative and Contracting Neural Ordinary Differential Equations

Hardware-Software Co-design for Improved Resource Utilization in DNN Accelerators

Predicting nonlinear optical scattering with physics-driven neural networks

Sparse Attacks for Manipulating Explanations in Deep Neural Network Models

From Prediction to Prevention: Leveraging Deep Learning in Traffic Accident Prediction Systems

DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications

Improved calorimetric particle identification in NA62 using machine learning techniques

Exploring neural networks and their potential for species distribution modeling

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks