Conforming and nonconforming virtual element methods for elliptic problems A Cangiani, G Manzini, OJ Sutton
IMA Journal of Numerical Analysis 37 (3), 1317-1354, 2017
260 2017 A posteriori error estimates for the virtual element method A Cangiani, EH Georgoulis, T Pryer, OJ Sutton
Numerische mathematik 137, 857-893, 2017
236 2017 Introduction to k nearest neighbour classification and condensed nearest neighbour data reduction O Sutton
University lectures, University of Leicester, 2012
192 2012 The virtual element method in 50 lines of MATLAB OJ Sutton
Numerical Algorithms 75, 1141-1159, 2017
102 2017 Virtual element methods for elliptic problems on polygonal meshes A Cangiani, OJ Sutton, V Gyrya, G Manzini
Generalized Barycentric Coordinates in Computer Graphics and Computational …, 2017
25 2017 Revealing new dynamical patterns in a reaction–diffusion model with cyclic competition via a novel computational framework A Cangiani, EH Georgoulis, AY Morozov, OJ Sutton
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2018
24 2018 Long-time L ∞ (L 2 ) a posteriori error estimates for fully discrete parabolic problems OJ Sutton
IMA Journal of Numerical Analysis 40 (1), 498-529, 2020
11 2020 Adaptive non-hierarchical Galerkin methods for parabolic problems with application to moving mesh and virtual element methods A Cangiani, EH Georgoulis, OJ Sutton
Mathematical Models and Methods in Applied Sciences 31 (04), 711-751, 2021
10 2021 Virtual element methods OJ Sutton
University of Leicester, 2017
6 2017 Residual-Based A Posteriori Error Estimates for Z Dong, L Mascotto, OJ Sutton
SIAM Journal on Numerical Analysis 59 (3), 1273-1298, 2021
5 2021 Efficient high-order space-angle-energy polytopic discontinuous Galerkin finite element methods for linear Boltzmann transport P Houston, ME Hubbard, TJ Radley, OJ Sutton, RSJ Widdowson
Journal of Scientific Computing 100 (2), 52, 2024
4 2024 The Conforming Virtual Element Method for the convection-diffusion-reaction equation with variable coeffcients. G Manzini, A Cangiani, O Sutton
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2014
4 2014 The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning A Bastounis, AN Gorban, AC Hansen, DJ Higham, D Prokhorov, O Sutton, ...
International Conference on Artificial Neural Networks, 530-541, 2023
3 2023 Towards a mathematical understanding of learning from few examples with nonlinear feature maps OJ Sutton, AN Gorban, IY Tyukin
arXiv preprint arXiv:2211.03607, 2022
3 2022 Relative Intrinsic Dimensionality Is Intrinsic to Learning OJ Sutton, Q Zhou, AN Gorban, IY Tyukin
International Conference on Artificial Neural Networks, 516-529, 2023
2 2023 How adversarial attacks can disrupt seemingly stable accurate classifiers OJ Sutton, Q Zhou, IY Tyukin, AN Gorban, A Bastounis, DJ Higham
arXiv preprint arXiv:2309.03665, 2023
1 2023 Learning from few examples with nonlinear feature maps IY Tyukin, O Sutton, AN Gorban
Science and Information Conference, 210-225, 2023
1 2023 Stealth edits for provably fixing or attacking large language models OJ Sutton, Q Zhou, W Wang, DJ Higham, AN Gorban, A Bastounis, ...
arXiv preprint arXiv:2406.12670, 2024
2024 Coping with AI Errors with Provable Guarantees IY Tyukin, T Tyukina, DP van Helden, Z Zheng, EM Mirkes, OJ Sutton, ...
Information Sciences, 120856, 2024
2024 Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees IY Tyukin, T Tyukina, D van Helden, Z Zhang, EM Mirkes, OJ Sutton, ...
arXiv preprint arXiv:2402.00899, 2024
2024 
Andrea CangianiAssociate Professor, Mathematics Area, SISSAE-mail megerősítve itt: sissa.it
