
Separation and Concentration in Deep Networks
Numerical experiments demonstrate that deep neural network classifiers p...
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Particle gradient descent model for point process generation
This paper introduces a generative model for planar point processes in a...
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Maximum Entropy Models from Phase Harmonic Covariances
We define maximum entropy models of nonGaussian stationary random vecto...
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Deep Network classification by Scattering and Homotopy dictionary learning
We introduce a sparse scattering deep convolutional neural network, whic...
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Kymatio: Scattering Transforms in Python
The wavelet scattering transform is an invariant signal representation s...
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Statistical learning of geometric characteristics of wireless networks
Motivated by the prediction of cell loads in cellular networks, we formu...
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Phase Harmonics and Correlation Invariants in Convolutional Neural Networks
We prove that linear rectifiers act as phase transformations on complex ...
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Classification with Joint TimeFrequency Scattering
In time series classification, signals are typically mapped into some in...
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Generative networks as inverse problems with Scattering transforms
Generative Adversarial Nets (GANs) and Variational AutoEncoders (VAEs) ...
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Solid Harmonic Wavelet Scattering for Predictions of Molecule Properties
We present a machine learning algorithm for the prediction of molecule p...
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Multiscale Sparse Microcanonical Models
We study density estimation of stationary processes defined over an infi...
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Multiscale Hierarchical Convolutional Networks
Deep neural network algorithms are difficult to analyze because they lac...
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Wavelet Scattering Regression of Quantum Chemical Energies
We introduce multiscale invariant dictionaries to estimate quantum chemi...
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Understanding Deep Convolutional Networks
Deep convolutional networks provide state of the art classifications and...
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Wavelet Scattering on the Pitch Spiral
We present a new representation of harmonic sounds that linearizes the d...
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Joint TimeFrequency Scattering for Audio Classification
We introduce the joint timefrequency scattering transform, a time shift...
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Transformée en scattering sur la spirale tempschromaoctave
We introduce a scattering representation for the analysis and classifica...
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Quantum Energy Regression using Scattering Transforms
We present a novel approach to the regression of quantum mechanical ener...
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Deep RotoTranslation Scattering for Object Classification
Dictionary learning algorithms or supervised deep convolution networks h...
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Unsupervised Deep Haar Scattering on Graphs
The classification of highdimensional data defined on graphs is particu...
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Generic Deep Networks with Wavelet Scattering
We introduce a twolayer wavelet scattering network, for object classifi...
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Wavelet methods for shape perception in electrosensing
This paper aims at presenting a new approach to the electrosensing prob...
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Deep Learning by Scattering
We introduce general scattering transforms as mathematical models of dee...
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Classification with Invariant Scattering Representations
A scattering transform defines a signal representation which is invarian...
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Geometric Models with Cooccurrence Groups
A geometric model of sparse signal representations is introduced for cla...
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Group Invariant Scattering
This paper constructs translation invariant operators on L2(R^d), which ...
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Classification with Scattering Operators
A scattering vector is a local descriptor including multiscale and multi...
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Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity
A general framework for solving image inverse problems is introduced in ...
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Stéphane Mallat
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Professor of Applied Mathematics and Computer Science, École Normale Supérieure