Model-based deep learning solutions to inverse problems have attracted
i...
We investigate to what extent it is possible to solve linear inverse pro...
Noise-shaping quantization techniques are widely used for converting
ban...
In this paper, we study the problem of recovering two unknown signals fr...
One of the most prominent methods for uncertainty quantification in
high...
Efficient surrogate modelling is a key requirement for uncertainty
quant...
In this paper, we study error diffusion techniques for digital halftonin...
The Unlimited Sensing Framework (USF) was recently introduced to overcom...
We prove the Johnson-Lindenstrauss property for matrices Φ D_ξ where
Φ h...
Low-rank matrix recovery problems arise naturally as mathematical
formul...
Given an arbitrary matrix A∈ℝ^n× n, we consider the
fundamental problem ...
Following the Unlimited Sampling strategy to alleviate the omnipresent
d...
Recently, experiments have been reported where researchers were able to
...
In this paper, we present modifications of the iterative hard thresholdi...
We prove new results about the robustness of well-known convex noise-bli...
In this paper a sublinear time algorithm is presented for the reconstruc...
We construct high order low-bit Sigma-Delta (ΣΔ) quantizers for
the vect...
The angular synchronization problem of estimating a set of unknown angle...
Ptychography, a special case of the phase retrieval problem, is a popula...
The problem of identifying a dynamical system from its dynamics is of gr...
We study the geometry of centrally-symmetric random polytopes, generated...
Phase retrieval refers to the problem of reconstructing an unknown vecto...
Shannon's sampling theorem is one of the cornerstone topics that is well...
Low-rank matrix recovery from structured measurements has been a topic o...
This paper studies the problem of recovering a signal from one-bit compr...
The idea of compressed sensing is to exploit representations in suitable...
In many applications, one is faced with an inverse problem, where the kn...
We introduce a new fast construction of a Johnson-Lindenstrauss matrix b...
In many signal processing applications, one wishes to acquire images tha...