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20102024
most citedOn instabilities of deep learning in image reconstruction - Does AI come at a cost?

795 citations · 1.4k across the 64 of their papers we have counts for

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Showing 2014Show all

8 papers · 1 filter

math.NA2014★ 1 cited

Density theorems for nonuniform sampling of bandlimited functions using derivatives or bunched measurements

Ben Adcock, Milana Gataric, Anders C. Hansen

We provide sufficient density condition for a set of nonuniform samples to give rise to a set of sampling for multivariate bandlimited functions when the measurements consist of po…

math.NA2014

Recovering piecewise smooth functions from nonuniform Fourier measurements

Ben Adcock, Milana Gataric, Anders C. Hansen

In this paper, we consider the problem of reconstructing piecewise smooth functions to high accuracy from nonuniform samples of their Fourier transform. We use the framework of non…

math.FA2014★ 78 cited

On asymptotic structure in compressed sensing

Bogdan Roman, Anders Hansen, Ben Adcock

This paper demonstrates how new principles of compressed sensing, namely asymptotic incoherence, asymptotic sparsity and multilevel sampling, can be utilised to better understand u…

math.NA2014★ 17 cited

Parameter selection and numerical approximation properties of Fourier extensions from fixed data

Ben Adcock, Joseph Ruan

Fourier extensions have been shown to be an effective means for the approximation of smooth, nonperiodic functions on bounded intervals given their values on an equispaced, or in g…

math.NA2014★ 3 cited

Weighted frames of exponentials and stable recovery of multidimensional functions from nonuniform Fourier samples

Ben Adcock, Milana Gataric, Anders C. Hansen

In this paper, we consider the problem of recovering a compactly supported multivariate function from a collection of pointwise samples of its Fourier transform taken nonuniformly.…

math.FA2014

The quest for optimal sampling: Computationally efficient, structure-exploiting measurements for compressed sensing

Ben Adcock, Anders C. Hansen, Bogdan Roman

An intriguing phenomenon in many instances of compressed sensing is that the reconstruction quality is governed not just by the overall sparsity of the signal, but also on its stru…

math.FA2014★ 2 cited

Linear Stable Sampling Rate: Optimality of 2D Wavelet Reconstructions from Fourier Measurements

Ben Adcock, Anders C. Hansen, Gitta Kutyniok +1

In this paper we analyze two-dimensional wavelet reconstructions from Fourier samples within the framework of generalized sampling. For this, we consider both separable compactly-s…

math.FA2014★ 7 cited

A note on compressed sensing of structured sparse wavelet coefficients from subsampled Fourier measurements

Ben Adcock, Anders C. Hansen, Bogdan Roman

This note complements the paper "The quest for optimal sampling: Computationally efficient, structure-exploiting measurements for compressed sensing" [2]. Its purpose is to present…