Stéphane Mallat

research

∙ 06/29/2023

Scattering Spectra Models for Physics

Physicists routinely need probabilistic models for a number of tasks suc...

0 Sihao Cheng, et al. ∙

research

∙ 05/31/2023

Conditionally Strongly Log-Concave Generative Models

There is a growing gap between the impressive results of deep image gene...

0 Florentin Guth, et al. ∙

research

∙ 05/29/2023

A Rainbow in Deep Network Black Boxes

We introduce rainbow networks as a probabilistic model of trained deep n...

0 Florentin Guth, et al. ∙

research

∙ 03/06/2023

Learning multi-scale local conditional probability models of images

Deep neural networks can learn powerful prior probability models for ima...

0 Zahra Kadkhodaie, et al. ∙

research

∙ 08/09/2022

Wavelet Score-Based Generative Modeling

Score-based generative models (SGMs) synthesize new data samples from Ga...

9 Florentin Guth, et al. ∙

research

∙ 07/11/2022

Wavelet Conditional Renormalization Group

We develop a multiscale approach to estimate high-dimensional probabilit...

18 Tanguy Marchand, et al. ∙

research

∙ 04/19/2022

Scale Dependencies and Self-Similarity Through Wavelet Scattering Covariance

We introduce a scattering covariance matrix which provides non-Gaussian ...

4 Rudy Morel, et al. ∙

research

∙ 04/15/2022

Wavelet Moments for Cosmological Parameter Estimation

Extracting non-Gaussian information from the non-linear regime of struct...

0 Michael Eickenberg, et al. ∙

research

∙ 03/14/2022

Generalized Rectifier Wavelet Covariance Models For Texture Synthesis

State-of-the-art maximum entropy models for texture synthesis are built ...

8 Antoine Brochard, et al. ∙

research

∙ 10/11/2021

Phase Collapse in Neural Networks

Deep convolutional image classifiers progressively transform the spatial...

15 Florentin Guth, et al. ∙

research

∙ 12/18/2020

Separation and Concentration in Deep Networks

Numerical experiments demonstrate that deep neural network classifiers p...

17 John Zarka, et al. ∙

research

∙ 10/27/2020

Particle gradient descent model for point process generation

This paper introduces a generative model for planar point processes in a...

12 Antoine Brochard, et al. ∙

research

∙ 11/22/2019

Maximum Entropy Models from Phase Harmonic Covariances

We define maximum entropy models of non-Gaussian stationary random vecto...

7 Sixin Zhang, et al. ∙

research

∙ 10/08/2019

Deep Network classification by Scattering and Homotopy dictionary learning

We introduce a sparse scattering deep convolutional neural network, whic...

9 John Zarka, et al. ∙

research

∙ 12/28/2018

Kymatio: Scattering Transforms in Python

The wavelet scattering transform is an invariant signal representation s...

12 Mathieu Andreux, et al. ∙

research

∙ 12/19/2018

Statistical learning of geometric characteristics of wireless networks

Motivated by the prediction of cell loads in cellular networks, we formu...

0 Antoine Brochard, et al. ∙

research

∙ 10/29/2018

Phase Harmonics and Correlation Invariants in Convolutional Neural Networks

We prove that linear rectifiers act as phase transformations on complex ...

0 Stéphane Mallat, et al. ∙

research

∙ 07/24/2018

Classification with Joint Time-Frequency Scattering

In time series classification, signals are typically mapped into some in...

0 Joakim andén, et al. ∙

research

∙ 05/17/2018

Generative networks as inverse problems with Scattering transforms

Generative Adversarial Nets (GANs) and Variational Auto-Encoders (VAEs) ...

0 Tomas Angles, et al. ∙

research

∙ 05/01/2018

Solid Harmonic Wavelet Scattering for Predictions of Molecule Properties

We present a machine learning algorithm for the prediction of molecule p...

0 Michael Eickenberg, et al. ∙

research

∙ 01/06/2018

Multiscale Sparse Microcanonical Models

We study density estimation of stationary processes defined over an infi...

0 Joan Bruna, et al. ∙

research

∙ 03/12/2017

Multiscale Hierarchical Convolutional Networks

Deep neural network algorithms are difficult to analyze because they lac...

0 Jörn-Henrik Jacobsen, et al. ∙

research

∙ 05/16/2016

Wavelet Scattering Regression of Quantum Chemical Energies

We introduce multiscale invariant dictionaries to estimate quantum chemi...

0 Matthew Hirn, et al. ∙

research

∙ 01/19/2016

Understanding Deep Convolutional Networks

Deep convolutional networks provide state of the art classifications and...

0 Stéphane Mallat, et al. ∙

research

∙ 01/03/2016

Wavelet Scattering on the Pitch Spiral

We present a new representation of harmonic sounds that linearizes the d...

0 Vincent Lostanlen, et al. ∙

research

∙ 12/07/2015

Joint Time-Frequency Scattering for Audio Classification

We introduce the joint time-frequency scattering transform, a time shift...

0 Joakim andén, et al. ∙

research

∙ 09/01/2015

Transformée en scattering sur la spirale temps-chroma-octave

We introduce a scattering representation for the analysis and classifica...

0 Vincent Lostanlen, et al. ∙

research

∙ 02/06/2015

Quantum Energy Regression using Scattering Transforms

We present a novel approach to the regression of quantum mechanical ener...

0 Matthew Hirn, et al. ∙

research

∙ 12/30/2014

Deep Roto-Translation Scattering for Object Classification

Dictionary learning algorithms or supervised deep convolution networks h...

0 Edouard Oyallon, et al. ∙

research

∙ 06/09/2014

Unsupervised Deep Haar Scattering on Graphs

The classification of high-dimensional data defined on graphs is particu...

0 Xu Chen, et al. ∙

research

∙ 12/20/2013

Generic Deep Networks with Wavelet Scattering

We introduce a two-layer wavelet scattering network, for object classifi...

0 Edouard Oyallon, et al. ∙

research

∙ 10/10/2013

Wavelet methods for shape perception in electro-sensing

This paper aims at presenting a new approach to the electro-sensing prob...

0 Habib Ammari, et al. ∙

research

∙ 06/24/2013

Deep Learning by Scattering

We introduce general scattering transforms as mathematical models of dee...

0 Stéphane Mallat, et al. ∙

research

∙ 12/05/2011

Classification with Invariant Scattering Representations

A scattering transform defines a signal representation which is invarian...

0 Joan Bruna, et al. ∙

research

∙ 01/30/2011

Geometric Models with Co-occurrence Groups

A geometric model of sparse signal representations is introduced for cla...

0 Joan Bruna, et al. ∙

research

∙ 01/12/2011

Group Invariant Scattering

This paper constructs translation invariant operators on L2(R^d), which ...

0 Stéphane Mallat, et al. ∙

research

∙ 11/12/2010

Classification with Scattering Operators

A scattering vector is a local descriptor including multiscale and multi...

0 Joan Bruna, et al. ∙

research

∙ 06/15/2010

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 ...

0 Guoshen Yu, et al. ∙

Stéphane Mallat

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