5 papers · 1 filter
A Hybrid Scattering Transform for Signals with Isolated Singularities
Michael Perlmutter, Jieqian He, Mark Iwen +1
The scattering transform is a wavelet-based model of Convolutional Neural Networks originally introduced by S. Mallat. Mallat's analysis shows that this network has desirable stabi…
On audio enhancement via online non-negative matrix factorization
Andrew Sack, Wenzhao Jiang, Michael Perlmutter +2
We propose a method for noise reduction, the task of producing a clean audio signal from a recording corrupted by additive noise. Many common approaches to this problem are based u…
Modewise Operators, the Tensor Restricted Isometry Property, and Low-Rank Tensor Recovery
Mark A. Iwen, Deanna Needell, Michael Perlmutter +1
Recovery of sparse vectors and low-rank matrices from a small number of linear measurements is well-known to be possible under various model assumptions on the measurements. The ke…
Phase Retrieval for via the Provably Accurate and Noise Robust Numerical Inversion of Spectrogram Measurements
Mark Iwen, Michael Perlmutter, Nada Sissouno +1
In this paper, we focus on the approximation of smooth functions , up to an unresolvable global phase ambiguity, from a finite set of Short Time…
MagNet: A Neural Network for Directed Graphs
Xitong Zhang, Yixuan He, Nathan Brugnone +2
The prevalence of graph-based data has spurred the rapid development of graph neural networks (GNNs) and related machine learning algorithms. Yet, despite the many datasets natural…