708 citations · 2.8k across the 48 of their papers we have counts for
6 papers · 1 filter
Generic Deep Networks with Wavelet Scattering
Edouard Oyallon, Stéphane Mallat, Laurent Sifre
We introduce a two-layer wavelet scattering network, for object classification. This scattering transform computes a spatial wavelet transform on the first layer and a new joint wa…
Audio Texture Synthesis with Scattering Moments
Joan Bruna, Stéphane Mallat
We introduce an audio texture synthesis algorithm based on scattering moments. A scattering transform is computed by iteratively decomposing a signal with complex wavelet filter ba…
Intermittent process analysis with scattering moments
Joan Bruna, Stéphane Mallat, Emmanuel Bacry +1
Scattering moments provide nonparametric models of random processes with stationary increments. They are expected values of random variables computed with a nonexpansive operator,…
Wavelet methods for shape perception in electro-sensing
Habib Ammari, Stéphane Mallat, Irène Waldspurger +1
This paper aims at presenting a new approach to the electro-sensing problem using wavelets. It provides an efficient algorithm for recognizing the shape of a target from micro-elec…
Deep Learning by Scattering
Stéphane Mallat, Irène Waldspurger
We introduce general scattering transforms as mathematical models of deep neural networks with l2 pooling. Scattering networks iteratively apply complex valued unitary operators, a…
Deep Scattering Spectrum
Joakim Andén, Stéphane Mallat
A scattering transform defines a locally translation invariant representation which is stable to time-warping deformations. It extends MFCC representations by computing modulation…