research
∙
06/29/2023
Scattering Spectra Models for Physics
Physicists routinely need probabilistic models for a number of tasks suc...
share
research
∙
05/31/2023
Conditionally Strongly Log-Concave Generative Models
There is a growing gap between the impressive results of deep image gene...
research
∙
05/29/2023
A Rainbow in Deep Network Black Boxes
We introduce rainbow networks as a probabilistic model of trained deep n...
research
∙
03/06/2023
Learning multi-scale local conditional probability models of images
Deep neural networks can learn powerful prior probability models for ima...
research
∙
08/09/2022
Wavelet Score-Based Generative Modeling
Score-based generative models (SGMs) synthesize new data samples from Ga...
research
∙
07/11/2022
Wavelet Conditional Renormalization Group
We develop a multiscale approach to estimate high-dimensional probabilit...
research
∙
04/19/2022
Scale Dependencies and Self-Similarity Through Wavelet Scattering Covariance
We introduce a scattering covariance matrix which provides non-Gaussian ...
research
∙
04/15/2022
Wavelet Moments for Cosmological Parameter Estimation
Extracting non-Gaussian information from the non-linear regime of struct...
research
∙
03/14/2022
Generalized Rectifier Wavelet Covariance Models For Texture Synthesis
State-of-the-art maximum entropy models for texture synthesis are built ...
research
∙
10/11/2021
Phase Collapse in Neural Networks
Deep convolutional image classifiers progressively transform the spatial...
research
∙
12/18/2020
Separation and Concentration in Deep Networks
Numerical experiments demonstrate that deep neural network classifiers p...
research
∙
10/27/2020
Particle gradient descent model for point process generation
This paper introduces a generative model for planar point processes in a...
research
∙
11/22/2019
Maximum Entropy Models from Phase Harmonic Covariances
We define maximum entropy models of non-Gaussian stationary random vecto...
research
∙
10/08/2019
Deep Network classification by Scattering and Homotopy dictionary learning
We introduce a sparse scattering deep convolutional neural network, whic...
research
∙
12/28/2018
Kymatio: Scattering Transforms in Python
The wavelet scattering transform is an invariant signal representation s...
research
∙
12/19/2018
Statistical learning of geometric characteristics of wireless networks
Motivated by the prediction of cell loads in cellular networks, we formu...
research
∙
10/29/2018
Phase Harmonics and Correlation Invariants in Convolutional Neural Networks
We prove that linear rectifiers act as phase transformations on complex ...
research
∙
07/24/2018
Classification with Joint Time-Frequency Scattering
In time series classification, signals are typically mapped into some in...
research
∙
05/17/2018
Generative networks as inverse problems with Scattering transforms
Generative Adversarial Nets (GANs) and Variational Auto-Encoders (VAEs) ...
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...
research
∙
01/06/2018
Multiscale Sparse Microcanonical Models
We study density estimation of stationary processes defined over an infi...
research
∙
03/12/2017
Multiscale Hierarchical Convolutional Networks
Deep neural network algorithms are difficult to analyze because they lac...
research
∙
05/16/2016
Wavelet Scattering Regression of Quantum Chemical Energies
We introduce multiscale invariant dictionaries to estimate quantum chemi...
research
∙
01/19/2016
Understanding Deep Convolutional Networks
Deep convolutional networks provide state of the art classifications and...
research
∙
01/03/2016
Wavelet Scattering on the Pitch Spiral
We present a new representation of harmonic sounds that linearizes the d...
research
∙
12/07/2015
Joint Time-Frequency Scattering for Audio Classification
We introduce the joint time-frequency scattering transform, a time shift...
research
∙
09/01/2015
Transformée en scattering sur la spirale temps-chroma-octave
We introduce a scattering representation for the analysis and classifica...
research
∙
02/06/2015
Quantum Energy Regression using Scattering Transforms
We present a novel approach to the regression of quantum mechanical ener...
research
∙
12/30/2014
Deep Roto-Translation Scattering for Object Classification
Dictionary learning algorithms or supervised deep convolution networks h...
research
∙
06/09/2014
Unsupervised Deep Haar Scattering on Graphs
The classification of high-dimensional data defined on graphs is particu...
research
∙
12/20/2013
Generic Deep Networks with Wavelet Scattering
We introduce a two-layer wavelet scattering network, for object classifi...
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...
research
∙
06/24/2013
Deep Learning by Scattering
We introduce general scattering transforms as mathematical models of dee...
research
∙
12/05/2011
Classification with Invariant Scattering Representations
A scattering transform defines a signal representation which is invarian...
research
∙
01/30/2011
Geometric Models with Co-occurrence Groups
A geometric model of sparse signal representations is introduced for cla...
research
∙
01/12/2011
Group Invariant Scattering
This paper constructs translation invariant operators on L2(R^d), which ...
research
∙
11/12/2010
Classification with Scattering Operators
A scattering vector is a local descriptor including multiscale and multi...
research
∙
06/15/2010