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09/18/2023
Graph topological property recovery with heat and wave dynamics-based features on graphs
In this paper, we propose Graph Differential Equation Network (GDeNet), ...
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09/14/2023
Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis
Directed graphs are a natural model for many phenomena, in particular sc...
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07/31/2023
A Flow Artist for High-Dimensional Cellular Data
We consider the problem of embedding point cloud data sampled from an un...
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07/08/2023
Manifold Filter-Combine Networks
We introduce a class of manifold neural networks (MNNs) that we call Man...
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12/23/2022
A Convergence Rate for Manifold Neural Networks
High-dimensional data arises in numerous applications, and the rapidly d...
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11/24/2022
Multi-scale Hybridized Topic Modeling: A Pipeline for Analyzing Unstructured Text Datasets via Topic Modeling
We propose a multi-scale hybridized topic modeling method to find hidden...
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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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08/15/2022
Learnable Filters for Geometric Scattering Modules
We propose a new graph neural network (GNN) module, based on relaxations...
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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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06/03/2022
Can Hybrid Geometric Scattering Networks Help Solve the Maximal Clique Problem?
We propose a geometric scattering-based graph neural network (GNN) for a...
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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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12/20/2021
Toward Fast and Provably Accurate Near-field Ptychographic Phase Retrieval
Ptychography is an imaging technique which involves a sample being illum...
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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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10/07/2021
On audio enhancement via online non-negative matrix factorization
We propose a method for noise reduction, the task of producing a clean a...
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09/21/2021
Modewise Operators, the Tensor Restricted Isometry Property, and Low-Rank Tensor Recovery
Recovery of sparse vectors and low-rank matrices from a small number of ...
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06/04/2021
Phase Retrieval for L^2([-π,π]) via the Provably Accurate and Noise Robust Numerical Inversion of Spectrogram Measurements
In this paper, we focus on the approximation of smooth functions f: [-π,...
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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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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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07/24/2019
Inverting Spectrogram Measurements via Aliased Wigner Distribution Deconvolution and Angular Synchronization
We propose a two-step approach for reconstructing a signal x∈C^d from s...
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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