Matthew Thorpe
Matthew Thorpe
Associate Professor in Statistics, University of Warwick
Geverifieerd e-mailadres voor warwick.ac.uk - Homepage
Geciteerd door
Geciteerd door
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ...
Nature Machine Intelligence 3 (3), 199-217, 2021
Optimal mass transport: Signal processing and machine-learning applications
S Kolouri, SR Park, M Thorpe, D Slepcev, GK Rohde
IEEE signal processing magazine 34 (4), 43-59, 2017
Analysis of -Laplacian Regularization in Semisupervised Learning
D Slepcev, M Thorpe
SIAM Journal on Mathematical Analysis 51 (3), 2085-2120, 2019
Poisson learning: Graph based semi-supervised learning at very low label rates
J Calder, B Cook, M Thorpe, D Slepcev
International Conference on Machine Learning, 1306-1316, 2020
A Transportation Distance for Signal Analysis
M Thorpe, S Park, S Kolouri, GK Rohde, D Slepčev
Journal of mathematical imaging and vision 59, 187-210, 2017
Deep limits of residual neural networks
M Thorpe, Y van Gennip
arXiv preprint arXiv:1810.11741, 2018
SARS-CoV-2-specific nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination
F Liew, S Talwar, A Cross, BJ Willett, S Scott, N Logan, MK Siggins, ...
EBioMedicine 87, 2023
GRAND++: Graph neural diffusion with a source term
M Thorpe, TM Nguyen, H Xia, T Strohmer, A Bertozzi, S Osher, B Wang
International Conference on Learning Representation (ICLR), 2022
Large data and zero noise limits of graph-based semi-supervised learning algorithms
MM Dunlop, D Slepčev, AM Stuart, M Thorpe
Applied and Computational Harmonic Analysis 49 (2), 655-697, 2020
Transport-based analysis, modeling, and learning from signal and data distributions
S Kolouri, S Park, M Thorpe, D Slepčev, GK Rohde
arXiv preprint arXiv:1609.04767, 2016
Rates of convergence for Laplacian semi-supervised learning with low labeling rates
J Calder, D Slepčev, M Thorpe
Research in the Mathematical Sciences 10 (1), 10, 2023
Introduction to optimal transport
M Thorpe
Lecture Notes 3, 2019
Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ...
arXiv preprint arXiv:2008.06388, 2020
Convergence of the -Means Minimization Problem using -Convergence
M Thorpe, F Theil, AM Johansen, N Cade
SIAM Journal on Applied Mathematics 75 (6), 2444-2474, 2015
Sliced optimal partial transport
Y Bai, B Schmitzer, M Thorpe, S Kolouri
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ...
Common pitfalls and recommendations for using machine learning to detect and …, 2021
Asymptotic analysis of the Ginzburg–Landau functional on point clouds
M Thorpe, F Theil
Proceedings of the Royal Society of Edinburgh Section A: Mathematics 149 (2 …, 2019
The Linearized Hellinger--Kantorovich Distance
T Cai, J Cheng, B Schmitzer, M Thorpe
SIAM Journal on Imaging Sciences 15 (1), 45-83, 2022
Representing and learning high dimensional data with the optimal transport map from a probabilistic viewpoint
S Park, M Thorpe
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
Large data limit for a phase transition model with the p-Laplacian on point clouds
R Cristoferi, M Thorpe
European Journal of Applied Mathematics 31 (2), 185-231, 2020
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