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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 2013Show all

5 papers · 1 filter

math.NA2013★ 28 cited

Generalized sampling: stable reconstructions, inverse problems and compressed sensing over the continuum

Ben Adcock, Anders Hansen, Bogdan Roman +1

The purpose of this paper is to report on recent approaches to reconstruction problems based on analog, or in other words, infinite-dimensional, image and signal models. We describ…

math.NA2013★ 2 cited

On stable reconstructions from nonuniform Fourier measurements

Ben Adcock, Milana Gataric, Anders C. Hansen

We consider the problem of recovering a compactly-supported function from a finite collection of pointwise samples of its Fourier transform taking nonuniformly. First, we show that…

math.NA2013

New exponential variable transform methods for functions with endpoint singularities

Ben Adcock, Mark Richardson

The focus of this article is the approximation of functions which are analytic on a compact interval except at the endpoints. Typical numerical methods for approximating such funct…

cs.IT2013★ 64 cited

Breaking the coherence barrier: A new theory for compressed sensing

Ben Adcock, Anders C. Hansen, Clarice Poon +1

This paper provides an extension of compressed sensing which bridges a substantial gap between existing theory and its current use in real-world applications. It introduces a mathe…

math.NA2013★ 2 cited

Beyond consistent reconstructions: optimality and sharp bounds for generalized sampling, and application to the uniform resampling problem

Ben Adcock, Anders C. Hansen, Clarice Poon

Generalized sampling is a recently developed linear framework for sampling and reconstruction in separable Hilbert spaces. It allows one to recover any element in any finite-dimens…