10 citations · 10 across the 1 of their papers we have counts for
4 papers
A Sampling Theorem for Deconvolution in Two Dimensions
Joseph McDonald, Brett Bernstein, Carlos Fernandez-Granda
This work studies the problem of estimating a two-dimensional superposition of point sources or spikes from samples of their convolution with a Gaussian kernel. Our results show th…
Sparse Recovery Beyond Compressed Sensing: Separable Nonlinear Inverse Problems
Brett Bernstein, Sheng Liu, Chrysa Papadaniil +1
Extracting information from nonlinear measurements is a fundamental challenge in data analysis. In this work, we consider separable inverse problems, where the data are modeled as…
A Learning-Based Framework for Line-Spectra Super-resolution
Gautier Izacard, Brett Bernstein, Carlos Fernandez-Granda
We propose a learning-based approach for estimating the spectrum of a multisinusoidal signal from a finite number of samples. A neural-network is trained to approximate the spectra…
Deconvolution of Point Sources: A Sampling Theorem and Robustness Guarantees
Brett Bernstein, Carlos Fernandez-Granda
In this work we analyze a convex-programming method for estimating superpositions of point sources or spikes from nonuniform samples of their convolution with a known kernel. We co…