On the absence of the RIP in real-world applications of compressed sensing and the RIP in levels. - Alexander Bastounis; Anders C. Hansen (CoRR, 2014)

On the Absence of Uniform Recovery in Many Real-World Applications of Compressed Sensing and the Restricted Isometry Property and Nullspace Property in Levels. - Alexander Bastounis; Anders C. Hansen (SIAM J. Imaging Sci., 2017)

The mathematics of adversarial attacks in AI - Why deep learning is unstable despite the existence of stable neural networks. - Alexander Bastounis; Anders C. Hansen; Verner Vlacic (CoRR, 2021)

The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning. - Alexander Bastounis; Alexander N. Gorban; Anders C. Hansen; Desmond J. Higham; Danil V. Prokhorov; Oliver J. Sutton; Ivan Yu. Tyukin; Qinghua Zhou (ICANN (1), 2023)

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 (CoRR, 2023)

Stealth edits to large language models. - Oliver J. Sutton; Qinghua Zhou; Wei Wang 357; Desmond J. Higham; Alexander N. Gorban; Alexander Bastounis; Ivan Tyukin (NeurIPS, 2024)

Stealth edits for provably fixing or attacking large language models. - Oliver J. Sutton; Qinghua Zhou; Wei Wang 357; Desmond J. Higham; Alexander N. Gorban; Alexander Bastounis; Ivan Yu. Tyukin (CoRR, 2024)

On the consistent reasoning paradox of intelligence and optimal trust in AI: The power of 'I don't know'. - Alexander Bastounis; Paolo Campodonico; Mihaela van der Schaar; Ben Adcock; Anders C. Hansen (CoRR, 2024)

How adversarial attacks can disrupt seemingly stable accurate classifiers. - Oliver J. Sutton; Qinghua Zhou; Ivan Yu. Tyukin; Alexander N. Gorban; Alexander Bastounis; Desmond J. Higham (Neural Networks, 2024)