The troublesome kernel -- On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problems

5 January 2020

Papers citing "The troublesome kernel -- On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problems"

7 / 7 papers shown

Title
When can you trust feature selection? -- I: A condition-based analysis of LASSO and generalised hardness of approximation Alexander Bastounis Felipe Cucker Anders C. Hansen 8 2 0 18 Dec 2023
Computability of Optimizers Yunseok Lee Holger Boche Gitta Kutyniok 22 16 0 15 Jan 2023
Theoretical Perspectives on Deep Learning Methods in Inverse Problems Jonathan Scarlett Reinhard Heckel M. Rodrigues Paul Hand Yonina C. Eldar AI4CE 16 29 0 29 Jun 2022
Limitations of Deep Learning for Inverse Problems on Digital Hardware Holger Boche Adalbert Fono Gitta Kutyniok 19 25 0 28 Feb 2022
A review and experimental evaluation of deep learning methods for MRI reconstruction Arghya Pal Yogesh Rathi 3DV 26 41 0 17 Sep 2021
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 16 29 0 11 Dec 2020
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 250 5,813 0 08 Jul 2016