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2020 – today
- 2024
[i8]Tobias A. Opsahl, Vegard Antun:
Achieving Data Efficient Neural Networks with Hybrid Concept-based Models. CoRR abs/2408.07438 (2024)- 2023
- [i7]Johan S. Wind, Vegard Antun, Anders C. Hansen:
Implicit regularization in AI meets generalized hardness of approximation in optimization - Sharp results for diagonal linear networks. CoRR abs/2307.07410 (2023) - 2022
- [j1]Vegard Antun
:
Recovering Wavelet Coefficients from Binary Samples Using Fast Transforms. SIAM J. Sci. Comput. 44(3): 1315- (2022) - 2021
- [b1]Vegard Antun:
Stability and accuracy in compressive sensing and deep learning. University of Oslo, Norway, 2021 - [i6]Vegard Antun, Matthew J. Colbrook, Anders C. Hansen:
Can stable and accurate neural networks be computed? - On the barriers of deep learning and Smale's 18th problem. CoRR abs/2101.08286 (2021) - [i5]Vegard Antun:
Recovering wavelet coefficients from binary samples using fast transforms. CoRR abs/2106.00554 (2021) - 2020
- [i4]Nina M. Gottschling, Vegard Antun, Ben Adcock, Anders C. Hansen:
The troublesome kernel: why deep learning for inverse problems is typically unstable. CoRR abs/2001.01258 (2020)
2010 – 2019
- 2019
- [i3]Vegard Antun, Francesco Renna, Clarice Poon, Ben Adcock, Anders C. Hansen:
On instabilities of deep learning in image reconstruction - Does AI come at a cost? CoRR abs/1902.05300 (2019) - [i2]Ben Adcock, Vegard Antun, Anders C. Hansen:
Uniform recovery in infinite-dimensional compressed sensing and applications to structured binary sampling. CoRR abs/1905.00126 (2019) - [i1]Laura Thesing, Vegard Antun, Anders C. Hansen:
What do AI algorithms actually learn? - On false structures in deep learning. CoRR abs/1906.01478 (2019)
Coauthor Index
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