87 citations · 450 across the 34 of their papers we have counts for
4 papers · 1 filter
Bispectrum Unbiasing for Dilation-Invariant Multi-reference Alignment
Liping Yin, Anna Little, Matthew Hirn
Motivated by modern data applications such as cryo-electron microscopy, the goal of classic multi-reference alignment (MRA) is to recover an unknown signal $f: \mathbb{R} \to \math…
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…
Unbiasing Procedures for Scale-invariant Multi-reference Alignment
Matthew Hirn, Anna Little
This article discusses a generalization of the 1-dimensional multi-reference alignment problem. The goal is to recover a hidden signal from many noisy observations, where each nois…
Wavelet invariants for statistically robust multi-reference alignment
Matthew Hirn, Anna Little
We propose a nonlinear, wavelet based signal representation that is translation invariant and robust to both additive noise and random dilations. Motivated by the multi-reference a…