708 citations · 2.8k across the 48 of their papers we have counts for
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Statistical learning of geometric characteristics of wireless networks
Antoine Brochard, Bartłomiej Błaszczyszyn, Stéphane Mallat +1
Motivated by the prediction of cell loads in cellular networks, we formulate the following new, fundamental problem of statistical learning of geometric marks of point processes: A…
Kymatio: Scattering Transforms in Python
Mathieu Andreux, Tomás Angles, Georgios Exarchakis +15
The wavelet scattering transform is an invariant signal representation suitable for many signal processing and machine learning applications. We present the Kymatio software packag…
Phase Harmonic Correlations and Convolutional Neural Networks
Stéphane Mallat, Sixin Zhang, Gaspar Rochette
A major issue in harmonic analysis is to capture the phase dependence of frequency representations, which carries important signal properties. It seems that convolutional neural ne…
Joint Time-Frequency Scattering
Joakim Andén, Vincent Lostanlen, Stéphane Mallat
In time series classification and regression, signals are typically mapped into some intermediate representation used for constructing models. Since the underlying task is often in…
Generative networks as inverse problems with Scattering transforms
Tomás Angles, Stéphane Mallat
Generative Adversarial Nets (GANs) and Variational Auto-Encoders (VAEs) provide impressive image generations from Gaussian white noise, but the underlying mathematics are not well…
Solid Harmonic Wavelet Scattering for Predictions of Molecule Properties
Michael Eickenberg, Georgios Exarchakis, Matthew Hirn +2
We present a machine learning algorithm for the prediction of molecule properties inspired by ideas from density functional theory. Using Gaussian-type orbital functions, we create…