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

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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

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

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Three-dimensional tomography of red blood cells using deep learning

Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions

Supplementary Material - AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks

Crowding and the Architecture of the Visual System

Neural Anisotropy Directions

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

Shape Reconstruction by Learning Differentiable Surface Representations

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

Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization

Pretraining boosts out-of-domain robustness for pose estimation

Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions

Crowding and the Architecture of the Visual System

Shape Reconstruction by Learning Differentiable Surface Representations

Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization

Neural Anisotropy Directions

Supplementary Material - AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks

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

Three-dimensional tomography of red blood cells using deep learning

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

Pretraining boosts out-of-domain robustness for pose estimation