Ben Adcock
Cited by
Cited by
On instabilities of deep learning in image reconstruction and the potential costs of AI
V Antun, F Renna, C Poon, B Adcock, AC Hansen
Proceedings of the National Academy of Sciences 117 (48), 30088-30095, 2020
Breaking the coherence barrier: A new theory for compressed sensing
B Adcock, AC Hansen, C Poon, B Roman
Forum of Mathematics, Sigma 5, 2017
Generalized sampling and infinite-dimensional compressed sensing
B Adcock, AC Hansen
Foundations of Computational Mathematics 16 (5), 1263-1323, 2016
On asymptotic structure in compressed sensing
B Roman, A Hansen, B Adcock
arXiv preprint arXiv:1406.4178, 2014
A generalized sampling theorem for stable reconstructions in arbitrary bases
B Adcock, AC Hansen
Journal of Fourier Analysis and Applications 18 (4), 685-716, 2012
The quest for optimal sampling: Computationally efficient, structure-exploiting measurements for compressed sensing
B Adcock, AC Hansen, B Roman
Compressed Sensing and its Applications, 143-167, 2015
Stable reconstructions in Hilbert spaces and the resolution of the Gibbs phenomenon
B Adcock, AC Hansen
Applied and Computational Harmonic Analysis 32 (3), 357-388, 2012
On the numerical stability of Fourier extensions
B Adcock, D Huybrechs, J Martín-Vaquero
Foundations of Computational Mathematics 14 (4), 635-687, 2014
Beyond consistent reconstructions: optimality and sharp bounds for generalized sampling, and application to the uniform resampling problem
B Adcock, AC Hansen, C Poon
SIAM Journal on Mathematical Analysis 45 (5), 3132-3167, 2013
On instabilities of deep learning in image reconstruction-Does AI come at a cost?
V Antun, F Renna, C Poon, B Adcock, AC Hansen
arXiv preprint arXiv:1902.05300, 2019
Infinite-dimensional compressed sensing and function interpolation
B Adcock
Foundations of Computational Mathematics, 1-41, 2015
The troublesome kernel: why deep learning for inverse problems is typically unstable
NM Gottschling, V Antun, B Adcock, AC Hansen
arXiv preprint arXiv:2001.01258, 2020
Breaking the coherence barrier: asymptotic incoherence and asymptotic sparsity in compressed sensing
B Adcock, AC Hansen, C Poon, B Roman
arXiv preprint arXiv:1302.0561, 2013
Frames and numerical approximation
B Adcock, D Huybrechs
SIAM Review 61 (3), 443-473, 2019
Compressed sensing approaches for polynomial approximation of high-dimensional functions
B Adcock, S Brugiapaglia, CG Webster
Compressed Sensing and its Applications, 93-124, 2017
Efficient compressed sensing SENSE pMRI reconstruction with joint sparsity promotion
IY Chun, B Adcock, TM Talavage
IEEE transactions on medical imaging 35 (1), 354-368, 2015
Convergence acceleration of modified Fourier series in one or more dimensions
B Adcock
Mathematics of Computation 80 (273), 225-261, 2011
On the resolution power of Fourier extensions for oscillatory functions
B Adcock, D Huybrechs
Journal of Computational and Applied Mathematics 260, 312-336, 2014
Generalized sampling: stable reconstructions, inverse problems and compressed sensing over the continuum
B Adcock, A Hansen, B Roman, G Teschke
Advances in Imaging and Electron Physics 182, 187-279, 2014
The gap between theory and practice in function approximation with deep neural networks
B Adcock, N Dexter
SIAM Journal on Mathematics of Data Science 3 (2), 624-655, 2021
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