25 citations · 27 across the 5 of their papers we have counts for
3 papers · 1 filter
Spectral Norm of Convolutional Layers with Circular and Zero Paddings
Blaise Delattre, Quentin Barthélemy, Alexandre Allauzen
This paper leverages the use of \emph{Gram iteration} an efficient, deterministic, and differentiable method for computing spectral norm with an upper bound guarantee. Designed for…
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing
Blaise Delattre, Alexandre Araujo, Quentin Barthélemy +1
Real-life applications of deep neural networks are hindered by their unsteady predictions when faced with noisy inputs and adversarial attacks. The certified radius in this context…
Efficient Bound of Lipschitz Constant for Convolutional Layers by Gram Iteration
Blaise Delattre, Quentin Barthélemy, Alexandre Araujo +1
Since the control of the Lipschitz constant has a great impact on the training stability, generalization, and robustness of neural networks, the estimation of this value is nowaday…