Publications associées à Espace pseudo-euclidien

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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

Espace pseudo-euclidien

Graph Chatbot

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Geometric Learning: Leveraging differential geometry for learning and control

Anomalous and Chern topological waves in hyperbolic networks

Complex Representation Learning with Graph Convolutional Networks for Knowledge Graph Alignment

A structured prediction approach for robot imitation learning

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

Discount models

Relative, local and global dimension in complex networks

Fourier uniqueness and interpolation in Euclidean space

On discrete Fourier uniqueness sets in Euclidean space

Collapse-invariant properties of spaces equipped with signals or directions

Fourier uniqueness and interpolation in Euclidean space

Collapse-invariant properties of spaces equipped with signals or directions

A structured prediction approach for robot imitation learning

Geometric Learning: Leveraging differential geometry for learning and control

Anomalous and Chern topological waves in hyperbolic networks

Discount models

Relative, local and global dimension in complex networks

On discrete Fourier uniqueness sets in Euclidean space

Complex Representation Learning with Graph Convolutional Networks for Knowledge Graph Alignment

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