Publications associées à Geometry of adversarial robustness of deep networks: methods and applications

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Square Attack: a query-efficient black-box adversarial attack via random search

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

We propose the Square Attack, a new score-based black-box

l_2

and

l_\infty

adversarial attack that does not rely on local gradient information and thus is not affected by gradient masking. The Square Attack is based on a randomized search scheme where ...

2020

Geometry of adversarial robustness of deep networks: methods and applications

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Chattez avec Graph Search

Square Attack: a query-efficient black-box adversarial attack via random search

Constructing a provably adversarially-robust classifier from a high accuracy one

FeGAN: Scaling Distributed GANs

Shape Reconstruction by Learning Differentiable Surface Representations

A geometry-inspired decision-based attack

A geometry-inspired decision-based attack

A Geometry-Inspired Decision-Based Attack

SparseFool: a few pixels make a big difference

Biologically plausible deep learning – but how far can we go with shallow networks?

A jamming transition from under- to over-parametrization affects generalization in deep learning

A geometry-inspired decision-based attack

Constructing a provably adversarially-robust classifier from a high accuracy one

Biologically plausible deep learning – but how far can we go with shallow networks?

A Geometry-Inspired Decision-Based Attack

FeGAN: Scaling Distributed GANs

A jamming transition from under- to over-parametrization affects generalization in deep learning

Shape Reconstruction by Learning Differentiable Surface Representations

SparseFool: a few pixels make a big difference

A geometry-inspired decision-based attack

Square Attack: a query-efficient black-box adversarial attack via random search