The virtual element method in 50 lines of MATLAB. - Oliver J. Sutton (Numer. Algorithms, 2017)

A posteriori error estimates for the virtual element method. - Andrea Cangiani; Emmanuil H. Georgoulis; Tristan Pryer; Oliver J. Sutton (Numerische Mathematik, 2017)

Adaptive non-hierarchical Galerkin methods for parabolic problems with application to moving mesh and virtual element methods. - Andrea Cangiani; Emmanuil H. Georgoulis; Oliver J. Sutton (CoRR, 2020)

Residual-based a posteriori error estimates for hp-discontinuous Galerkin discretisations of the biharmonic problem. - Zhaonan Dong; Lorenzo Mascotto; Oliver J. Sutton (CoRR, 2020)

Residual-Based A Posteriori Error Estimates for hp-Discontinuous Galerkin Discretizations of the Biharmonic Problem. - Zhaonan Dong; Lorenzo Mascotto; Oliver J. Sutton (SIAM J. Numer. Anal., 2021)

Learning from few examples with nonlinear feature maps. - Ivan Yu. Tyukin; Oliver J. Sutton; Alexander N. Gorban (CoRR, 2022)

Towards a mathematical understanding of learning from few examples with nonlinear feature maps. - Oliver J. Sutton; Alexander N. Gorban; Ivan Yu. Tyukin (CoRR, 2022)

A Geometric View on the Role of Nonlinear Feature Maps in Few-Shot Learning. - Oliver J. Sutton; Alexander N. Gorban; Ivan Yu. Tyukin (GSI (1), 2023)

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)

Relative Intrinsic Dimensionality Is Intrinsic to Learning. - Oliver J. Sutton; Qinghua Zhou; Alexander N. Gorban; Ivan Yu. Tyukin (ICANN (1), 2023)

Neuromorphic tuning of feature spaces to overcome the challenge of low-sample high-dimensional data. - Qinghua Zhou; Oliver J. Sutton; Yudong Zhang 001; Alexander N. Gorban; Valeri A. Makarov; Ivan Yu. Tyukin (IJCNN, 2023)

Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees. - Ivan Yu. Tyukin; Tatiana Tyukina; Daniel van Helden; Zedong Zheng; Evgeny M. Mirkes; Oliver J. Sutton; Qinghua Zhou; Alexander N. Gorban; Penelope M. Allison (IJCNN, 2024)

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)

Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees. - Ivan Yu. Tyukin; Tatiana Tyukina; Daniël P. van Helden; Zedong Zheng; Evgeny M. Mirkes; Oliver J. Sutton; Qinghua Zhou; Alexander N. Gorban; Penelope M. Allison (CoRR, 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)

Coping with AI errors with provable guarantees. - Ivan Yu. Tyukin; Tatiana Tyukina; Daniël P. van Helden; Zedong Zheng; Evgeny M. Mirkes; Oliver J. Sutton; Qinghua Zhou; Alexander N. Gorban; Penelope M. Allison (Inf. Sci., 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)

Efficient High-Order Space-Angle-Energy Polytopic Discontinuous Galerkin Finite Element Methods for Linear Boltzmann Transport. - Paul Houston; Matthew E. Hubbard; Thomas J. Radley; Oliver J. Sutton; Richard S. J. Widdowson (J. Sci. Comput., 2024)

Staining and locking computer vision models without retraining. - Oliver J. Sutton; Qinghua Zhou; George Leete; Alexander N. Gorban; Ivan Yu. Tyukin (CoRR, 2025)