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Vegard Antun
Vegard Antun
Postdoctoral Fellow - University of Oslo
Verified email at math.uio.no - Homepage
Title
Cited by
Cited by
Year
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
6382020
The difficulty of computing stable and accurate neural networks: On the barriers of deep learning and Smale’s 18th problem
MJ Colbrook, V Antun, AC Hansen
Proceedings of the National Academy of Sciences 119, 2022
1262022
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
1012020
On assessing trustworthy AI in healthcare. Machine learning as a supportive tool to recognize cardiac arrest in emergency calls
RV Zicari, J Brusseau, SN Blomberg, HC Christensen, M Coffee, ...
Frontiers in Human Dynamics 3, 673104, 2021
272021
Uniform recovery in infinite-dimensional compressed sensing and applications to structured binary sampling
B Adcock, V Antun, AC Hansen
Applied and Computational Harmonic Analysis 55, 1-40, 2021
182021
The troublesome kernel--On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problems
NM Gottschling, V Antun, AC Hansen, B Adcock
arXiv preprint arXiv:2001.01258, 2020
162020
Coherence estimates between hadamard matrices and daubechies wavelets
V Antun
University of Oslo, 2016
162016
Proving existence is not enough: Mathematical paradoxes unravel the limits of neural networks in artificial intelligence
V Antun, MJ Colbrook, AC Hansen
SIAM News 55 (04), 1-4, 2022
102022
What do AI algorithms actually learn?-On false structures in deep learning
L Thesing, V Antun, AC Hansen
arXiv preprint arXiv:1906.01478, 2019
102019
Deep learning in scientific computing: Understanding the instability mystery
V Antun, NM Gottschling, AC Hansen, B Adcock
SIAM NEWS MARCH 2021, 8, 2021
72021
On instabilities of deep learning in image reconstruction—Does AI come at a cost? arXiv 2019
V Antun, F Renna, C Poon, B Adcock, AC Hansen
arXiv preprint arXiv:1902.05300, 0
6
Implicit regularization in AI meets generalized hardness of approximation in optimization--Sharp results for diagonal linear networks
JS Wind, V Antun, AC Hansen
arXiv preprint arXiv:2307.07410, 2023
42023
On the Unification of Schemes and Software for Wavelets on the Interval
V Antun, Ĝ Ryan
Acta Applicandae Mathematicae 173, 1-25, 2021
22021
Recovering wavelet coefficients from binary samples using fast transforms
V Antun
SIAM Journal on Scientific Computing 44 (3), A1315-A1336, 2022
12022
Uniform recovery guarantees for Hadamard sampling and wavelet reconstruction
V Antun, B Adcock, A Hansen, Ĝ Ryan
Signal Processing with Adaptive Sparse Structured Representations workshop …, 2017
12017
On the existence of stable and accurate neural networks for image reconstruction
MJ Colbrook, V Antun, AC Hansen
12009
On the existence of optimal multi-valued decoders and their accuracy bounds for undersampled inverse problems
NM Gottschling, P Campodonico, V Antun, AC Hansen
arXiv preprint arXiv:2311.16898, 2023
2023
On accuracy and existence of approximate decoders for ill-posed inverse problems
NM Gottschling, P Campodonico, V Antun, AC Hansen
2023
Mathematical paradoxes unearth the boundaries of AI
M Colbrook, V Antun, A Hansen
TheScienceBreaker 8 (3), 2022
2022
Stability and accuracy in compressive sensing and deep learning
V Antun
University of Oslo, 2020
2020
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