| 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 | 800 | 2020 |
| 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 | 185 | 2022 |
| 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 | 119 | 2020 |
| 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 | 46 | 2021 |
| The Troublesome Kernel: On Hallucinations, No Free Lunches, and the Accuracy-Stability Tradeoff in Inverse Problems NM Gottschling, V Antun, AC Hansen, B Adcock SIAM Review 67 (1), 73-104, 2025 | 30 | 2025 |
| 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 | 18 | 2021 |
| Coherence estimates between hadamard matrices and daubechies wavelets V Antun University of Oslo, 2016 | 16 | 2016 |
| What do AI algorithms actually learn?-On false structures in deep learning L Thesing, V Antun, AC Hansen arXiv preprint arXiv:1906.01478, 2019 | 11 | 2019 |
| Proving existence is not enough: Mathematical paradoxes unravel the limits of neural networks in artificial intelligence V Antun, MJ Colbrook, AC Hansen Collections 55 (04), 2022 | 10 | 2022 |
| Deep learning in scientific computing: Understanding the instability mystery V Antun, NM Gottschling, AC Hansen, B Adcock SIAM NEWS MARCH 2021, 2021 | 9 | 2021 |
| 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 | 8 | 2023 |
| 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 | 4 | |
| On the Unification of Schemes and Software for Wavelets on the Interval V Antun, Ø Ryan Acta Applicandae Mathematicae 173, 1-25, 2021 | 2 | 2021 |
| Recovering wavelet coefficients from binary samples using fast transforms V Antun SIAM Journal on Scientific Computing 44 (3), A1315-A1336, 2022 | 1 | 2022 |
| Stability and accuracy in compressive sensing and deep learning V Antun University of Oslo, 2020 | 1 | 2020 |
| Uniform recovery guarantees for Hadamard sampling and wavelet reconstruction V Antun, B Adcock, A Hansen, Ø Ryan Signal Processing with Adaptive Sparse Structured Representations workshop …, 2017 | 1 | 2017 |
| On the existence of stable and accurate neural networks for image reconstruction MJ Colbrook, V Antun, AC Hansen | 1 | 2009 |
| Achieving Data Efficient Neural Networks with Hybrid Concept-based Models TA Opsahl, V Antun arXiv preprint arXiv:2408.07438, 2024 | | 2024 |
| 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 |
Ben AdcockProfessor, Simon Fraser UniversityPotvrđena adresa e-pošte na sfu.ca
