Oliver J. Sutton

According to our database, Oliver J. Sutton authored at least 20 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Left shifting analysis of Human-Autonomous Team interactions to analyse risks of autonomy in high-stakes AI systems.

Ben Larwood, Oliver J. Sutton, Callum Cockburn

CoRR, December, 2025

Staining and Locking Computer Vision Models Without Retraining.

Oliver J. Sutton, Qinghua Zhou, George Leete, Alexander N. Gorban, Ivan Yu. Tyukin

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

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., August, 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

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

Stealth edits for provably fixing or attacking large language models.

Oliver J. Sutton, Qinghua Zhou, Wei Wang, Desmond J. Higham, Alexander N. Gorban, Alexander Bastounis, Ivan Yu. Tyukin

CoRR, 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 to large language models.

Oliver J. Sutton, Qinghua Zhou, Wei Wang, Desmond J. Higham, Alexander N. Gorban, Alexander Bastounis, Ivan Tyukin

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

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

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

Neuromorphic tuning of feature spaces to overcome the challenge of low-sample high-dimensional data.

Qinghua Zhou, Oliver J. Sutton, Yudong Zhang, Alexander N. Gorban, Valeri A. Makarov, Ivan Yu. Tyukin

Proceedings of the International Joint Conference on Neural Networks, 2023

Relative Intrinsic Dimensionality Is Intrinsic to Learning.

Oliver J. Sutton, Qinghua Zhou, Alexander N. Gorban, Ivan Yu. Tyukin

Proceedings of the Artificial Neural Networks and Machine Learning, 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

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

A Geometric View on the Role of Nonlinear Feature Maps in Few-Shot Learning.

Oliver J. Sutton, Alexander N. Gorban, Ivan Yu. Tyukin

Proceedings of the Geometric Science of Information - 6th International Conference, 2023

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

Learning from few examples with nonlinear feature maps.

Ivan Yu. Tyukin, Oliver J. Sutton, Alexander N. Gorban

CoRR, 2022

2021

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

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

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

2017

A posteriori error estimates for the virtual element method.

Andrea Cangiani, Emmanuil H. Georgoulis, Tristan Pryer, Oliver J. Sutton

Numerische Mathematik, 2017

The virtual element method in 50 lines of MATLAB.

Oliver J. Sutton

Numer. Algorithms, 2017