
Wavelet Scattering Networks for Atomistic Systems with Extrapolation of Material Properties
The dream of machine learning in materials science is for a model to lea...
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Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms
The scattering transform is a multilayered waveletbased deep learning a...
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Wavelet invariants for statistically robust multireference alignment
We propose a nonlinear, wavelet based signal representation that is tran...
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Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds
The Euclidean scattering transform was introduced nearly a decade ago to...
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Scattering Statistics of Generalized Spatial Poisson Point Processes
We present a machine learning model for the analysis of randomly generat...
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Geometric Scattering on Manifolds
We present a mathematical model for geometric deep learning based upon a...
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Graph Classification with Geometric Scattering
One of the most notable contributions of deep learning is the applicatio...
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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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Structural Risk Minimization for C^1,1(R^d) Regression
One means of fitting functions to highdimensional data is by providing ...
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Wavelet Scattering Regression of Quantum Chemical Energies
We introduce multiscale invariant dictionaries to estimate quantum chemi...
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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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Matthew Hirn
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