Vegard Antun
Postdoctoral Fellow
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Differential Equations and Computational Mathematics

Norwegian version of this page
Email
vegarant@math.uio.no
Mobile phone
+47 91553728
Room
1005
Username
Visiting address
Moltke Moes vei 35
Niels Henrik Abels hus
0851 OSLO
Postal address
Postboks 1053 Blindern
0316 Oslo
Academic interests
Inverse problems, compressive imaging, wavelets, deep learning, neural networks.
For more information see my webpage.
Publications
- V. Antun, M. J. Colbrook, A. C. Hansen. Proving Existence Is Not Enough: Mathematical Paradoxes Unravel the Limits of Neural Networks in Artificial Intelligence, SIAM News, 2022, 55 (4) 1-4.
- M. Colbrook, V. Antun, A. C. Hansen. The difficulty of computing stable and accurate neural networks: On the barriers of deep learning and Smale's 18th problem, Proc. Natl. Acad. Sci., USA, 2022, 119(12).
- V. Antun. Recovering wavelet coefficients from binary samples using fast transforms, (to appear in SIAM J. Sci. Comput.), [arXiv].
- V. Antun, Ø. Ryan. On the unification of schemes for and software wavelets on the interval. Acta Appl. Math., 2021. [Technical report]
- B. Adcock, V. Antun, A. C. Hansen. Uniform recovery in infinite-dimensional compressed sensing and applications to structured binary sampling. Appl. Comput. Harmon. Anal., 2021. (to appear) [arXiv].
- V. Antun, N. M. Gottschling, A. C. Hansen, B. Adcock. Deep Learning in Scientific Computing: Understanding the Instability Mystery. SIAM News, 2021.
- V. Antun, F. Renna, C. Poon, B. Adcock, A. C. Hansen. On instabilities of deep learning in image reconstruction and the potential costs of AI. Proc. Natl. Acad. Sci. USA, 2020. [arXiv]. In the news: [titan.uio.no], [datatech], [dagensmedisin], [Teknisk ukeblad] [digi], [Physics World], [Health Care Business], [Radiology Business], [The Register], [Science daily], [Psychology Today], [Government Computing], [Diagnostic Imaging], [News Medical], [Press Release Point], [Tech Xplore], [Aunt Minnie], [My Science], [Digit], [The Talking Machines], [Rama on Healthcare], [News8PLus], [Healthcare in Europe], [AuntminnieEurope], [AI Development Hub], [FirstWord MedTech], [AI daily], [Cam. Univ. News].
- R. V. Zicari, J. Brusseau, S. N. Blomberg • H. C. Christensen, M. Coffee, M. B. Ganapini, S. Gerke, T. K. Gilbert, E. Hickman, E. Hildt, S. Holm, U. Kühne, V. I. Madai, W. Osika, A. Spezzatti, E. Schnebel, J. J. Tithi, D. Vetter, M. Westerlund, R. Wurth. J. Amann, V. Antun, V. Beretta, F. Bruneault, E. Campano, B. Düdder, A. Gallucci, E. Goffi, C. B. Haase, T. Hagendorff, P. Kringen, F. Möslein, D. Ottenheimer, M. Ozols, L. Palazzani, M. Petrin, K. Tafur, J. Tørresen, H. Volland, G. Kararigas. On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls, Front. Hum. Dyn., 08 July 2021.
Preprints
- N. Gottschling, V. Antun, B. Adcock, A. C. Hansen. The troublesome kernel: why deep learning for inverse problems is typically unstable, [arXiv].
- L. Thesing, V. Antun, A. C. Hansen. What do AI algorithms actually learn? - On false structures in deep learning, [arXiv].
Refereed Conference Articles
- M. Colbrook, V. Antun, A. C. Hansen. On the existence of stable and accurate neural networks for image reconstruction, Signal Processing with Adaptive Sparse Structured
Representations (SPARS), 2019, [PDF].
PhD Thesis
- V. Antun. Stability and accuracy in compressive sensing and deep learning [pdf]
Courses taught
- Spring 2021: Lecturing MIEVU4020 – Introduction to Deep Learning
- Autumn 2020: Teaching assistant in MAT3110 – Introduction to Numerical Analysis
- Autumn 2019: Lecturing MAT-INF 1100 – Modelling and computations
- Autumn 2016-1018: Plenary exercises in MAT-INF 1100 – Modelling and computations
- Spring 2017: Teaching assistant in MAT-INF 2360 - Applications of linear algebra
Published Aug. 22, 2016 4:24 PM
- Last modified May 2, 2022 5:11 PM