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05/10/2023
NervePool: A Simplicial Pooling Layer
For deep learning problems on graph-structured data, pooling layers are ...
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08/17/2022
Geometric Scattering on Measure Spaces
The scattering transform is a multilayered, wavelet-based transform init...
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06/21/2022
The Manifold Scattering Transform for High-Dimensional Point Cloud Data
The manifold scattering transform is a deep feature extractor for data d...
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06/15/2022
Taxonomy of Benchmarks in Graph Representation Learning
Graph Neural Networks (GNNs) extend the success of neural networks to gr...
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03/28/2022
Time-inhomogeneous diffusion geometry and topology
Diffusion condensation is a dynamic process that yields a sequence of mu...
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01/22/2022
Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid Scattering Networks
Geometric deep learning (GDL) has made great strides towards generalizin...
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10/27/2021
Towards a Taxonomy of Graph Learning Datasets
Graph neural networks (GNNs) have attracted much attention due to their ...
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10/10/2021
A Hybrid Scattering Transform for Signals with Isolated Singularities
The scattering transform is a wavelet-based model of Convolutional Neura...
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09/15/2021
Accurately Modeling Biased Random Walks on Weighted Graphs Using Node2vec+
Node embedding is a powerful approach for representing the structural ro...
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07/02/2021
Unbiasing Procedures for Scale-invariant Multi-reference Alignment
This article discusses a generalization of the 1-dimensional multi-refer...
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05/22/2021
Texture synthesis via projection onto multiscale, multilayer statistics
We provide a new model for texture synthesis based on a multiscale, mult...
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02/22/2021
MagNet: A Magnetic Neural Network for Directed Graphs
The prevalence of graph-based data has spurred the rapid development of ...
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06/01/2020
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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11/14/2019
Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms
The scattering transform is a multilayered wavelet-based deep learning a...
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09/24/2019
Wavelet invariants for statistically robust multi-reference alignment
We propose a nonlinear, wavelet based signal representation that is tran...
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05/24/2019
Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds
The Euclidean scattering transform was introduced nearly a decade ago to...
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02/10/2019
Scattering Statistics of Generalized Spatial Poisson Point Processes
We present a machine learning model for the analysis of randomly generat...
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12/15/2018
Geometric Scattering on Manifolds
We present a mathematical model for geometric deep learning based upon a...
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10/07/2018
Graph Classification with Geometric Scattering
One of the most notable contributions of deep learning is the applicatio...
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05/01/2018
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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03/29/2018
Structural Risk Minimization for C^1,1(R^d) Regression
One means of fitting functions to high-dimensional data is by providing ...
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05/16/2016
Wavelet Scattering Regression of Quantum Chemical Energies
We introduce multiscale invariant dictionaries to estimate quantum chemi...
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02/06/2015