Matthew Thorpe

41 papers A* 5Journal 34Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Large Data Limits of Laplace Learning for Gaussian Measure Data in Infinite Dimensions. CoRR Zhengang Zhong, Yury Korolev, Matthew Thorpe
2025	J	`jnl`	Analysis of Semi-Supervised Learning on Hypergraphs. CoRR Adrien Weihs, Andrea L. Bertozzi, Matthew Thorpe
2025	A*	`conf`	Expected Sliced Transport Plans. ICLR Xinran Liu, Rocio Diaz Martin, Yikun Bai, Ashkan Shahbazi, Matthew Thorpe, Akram Aldroubi, Soheil Kolouri
2025	J	`jnl`	Higher-Order Regularization Learning on Hypergraphs. CoRR Adrien Weihs, Andrea L. Bertozzi, Matthew Thorpe
2025	J	`jnl`	Laplace Learning in Wasserstein Space. CoRR Mary Chriselda Antony Oliver, Michael Roberts, Carola-Bibiane Schönlieb, Matthew Thorpe
2025	J	`jnl`	Manifold Learning in Wasserstein Space. SIAM J. Math. Anal. Keaton Hamm, Caroline Moosmüller, Bernhard Schmitzer, Matthew Thorpe
2025	J	`jnl`	Uncertainty-Based Smooth Policy Regularisation for Reinforcement Learning with Few Demonstrations. CoRR Yujie Zhu, Charles A. Hepburn, Matthew Thorpe, Giovanni Montana
2024	J	`jnl`	A linear transportation Lp distance for pattern recognition. Pattern Recognit. Oliver M. Crook, Mihai Cucuringu, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis
2024	J	`jnl`	Consistency of Fractional Graph-Laplacian Regularization in Semisupervised Learning with Finite Labels. SIAM J. Math. Anal. Adrien Weihs, Matthew Thorpe
2024	J	`jnl`	Expected Sliced Transport Plans. CoRR Xinran Liu, Rocio Diaz Martin, Yikun Bai, Ashkan Shahbazi, Matthew Thorpe, Akram Aldroubi, Soheil Kolouri
2023	J	`jnl`	Discrete-to-Continuum Rates of Convergence for $p$-Laplacian Regularization. CoRR Adrien Weihs, Jalal Fadili, Matthew Thorpe
2023	J	`jnl`	Manifold learning in Wasserstein space. CoRR Keaton Hamm, Caroline Moosmüller, Bernhard Schmitzer, Matthew Thorpe
2023	J	`jnl`	Navigating the development challenges in creating complex data systems. Nat. Mac. Intell. Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, Ian Selby, Anna Breger, Matthew Thorpe, Jonathan R. Weir-McCall, Effrossyni Gkrania-Klotsas, Anna Korhonen, Emily R. Jefferson, Georg Langs, Guang Yang, Helmut Prosch, Jan Stanczuk, Jing Tang, Judith Babar, Lorena Escudero Sanchez, Philip Teare, Mishal Patel, Marcel Wassin, Markus Holzer, Nicholas Walton, Pietro Lió, Tolou Shadbahr, Evis Sala, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb
2023	J	`jnl`	PTL CoRR Xinran Liu, Yikun Bai, Huy Tran, Zhanqi Zhu, Matthew Thorpe, Soheil Kolouri
2023	A*	`conf`	Sliced Optimal Partial Transport. CVPR Yikun Bai, Bernhard Schmitzer, Matthew Thorpe, Soheil Kolouri
2022	J	`jnl`	Classification of datasets with imputed missing values: does imputation quality matter? CoRR Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian D. Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramón Viñas Torné, Evis Sala, Pietro Lió, Mishal Patel, AIX-COVNET Collaboration, James H. F. Rudd, Tuomas Mirtti, Antti Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb
2022	A*	`conf`	GRAND++: Graph Neural Diffusion with A Source Term. ICLR Matthew Thorpe, Tan Minh Nguyen, Hedi Xia, Thomas Strohmer, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2022	J	`jnl`	Rates of Convergence for Regression with the Graph Poly-Laplacian. CoRR Nicolás García Trillos, Ryan Murray, Matthew Thorpe
2022	J	`jnl`	Sliced Optimal Partial Transport. CoRR Yikun Bai, Bernhard Schmitzer, Matthew Thorpe, Soheil Kolouri
2022	J	`jnl`	The Linearized Hellinger-Kantorovich Distance. SIAM J. Imaging Sci. Tianji Cai, Junyi Cheng, Bernhard Schmitzer, Matthew Thorpe
2022	J	`jnl`	Γ-Convergence of an Ambrosio-Tortorelli approximation scheme for image segmentation. CoRR Irene Fonseca, Lisa Maria Kreusser, Carola-Bibiane Schönlieb, Matthew Thorpe
2021	J	`jnl`	Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nat. Mach. Intell. Michael Roberts, Derek Driggs, Matthew Thorpe, Julian D. Gilbey, Michael Yeung, Stephan Ursprung, Angelica I. Avilés-Rivero, Christian Etmann, Cathal McCague, Lucian Beer, Jonathan R. Weir-McCall, Zhongzhao Teng, Effrossyni Gkrania-Klotsas, James H. F. Rudd, Evis Sala, Carola-Bibiane Schönlieb
2021	—	`conf`	Robust Certification for Laplace Learning on Geometric Graphs. MSML Matthew Thorpe, Bao Wang
2021	J	`jnl`	Robust Certification for Laplace Learning on Geometric Graphs. CoRR Matthew Thorpe, Bao Wang
2020	J	`jnl`	A Linear Transportation L CoRR Oliver M. Crook, Mihai Cucuringu, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis
2020	J	`jnl`	From graph cuts to isoperimetric inequalities: Convergence rates of Cheeger cuts on data clouds. CoRR Nicolás García Trillos, Ryan Murray, Matthew Thorpe
2020	J	`jnl`	Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review. CoRR Michael Roberts, Derek Driggs, Matthew Thorpe, Julian D. Gilbey, Michael Yeung, Stephan Ursprung, Angelica I. Avilés-Rivero, Christian Etmann, Cathal McCague, Lucian Beer, Jonathan R. Weir-McCall, Zhongzhao Teng, James H. F. Rudd, Evis Sala, Carola-Bibiane Schönlieb
2020	A*	`conf`	Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates. ICML Jeff Calder, Brendan Cook, Matthew Thorpe, Dejan Slepcev
2020	J	`jnl`	Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates. CoRR Jeff Calder, Brendan Cook, Matthew Thorpe, Dejan Slepcev
2020	J	`jnl`	Rates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates. CoRR Jeff Calder, Dejan Slepcev, Matthew Thorpe
2019	J	`jnl`	Analysis of p-Laplacian Regularization in Semisupervised Learning. SIAM J. Math. Anal. Dejan Slepcev, Matthew Thorpe
2019	J	`jnl`	PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds. CoRR Oliver M. Crook, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis
2018	J	`jnl`	Large Data and Zero Noise Limits of Graph-Based Semi-Supervised Learning Algorithms. CoRR Matthew M. Dunlop, Dejan Slepcev, Andrew M. Stuart, Matthew Thorpe
2018	A*	`conf`	Representing and Learning High Dimensional Data With the Optimal Transport Map From a Probabilistic Viewpoint. CVPR Serim Park, Matthew Thorpe
2017	J	`jnl`	A Transportation L J. Math. Imaging Vis. Matthew Thorpe, Serim Park, Soheil Kolouri, Gustavo K. Rohde, Dejan Slepcev
2017	J	`jnl`	Analysis of $p$-Laplacian Regularization in Semi-Supervised Learning. CoRR Dejan Slepcev, Matthew Thorpe
2017	J	`jnl`	Optimal Mass Transport: Signal processing and machine-learning applications. IEEE Signal Process. Mag. Soheil Kolouri, Se Rim Park, Matthew Thorpe, Dejan Slepcev, Gustavo K. Rohde
2016	J	`jnl`	A Transportation L CoRR Matthew Thorpe, Serim Park, Soheil Kolouri, Gustavo K. Rohde, Dejan Slepcev
2016	J	`jnl`	Transport-based analysis, modeling, and learning from signal and data distributions. CoRR Soheil Kolouri, Serim Park, Matthew Thorpe, Dejan Slepcev, Gustavo K. Rohde
2015	J	`jnl`	Convergence of the k-Means Minimization Problem using Γ-Convergence. SIAM J. Appl. Math. Matthew Thorpe, Florian Theil, Adam M. Johansen, Neil Cade
2014	—	`conf`	Self-reinforced Meta Learning for Belief Generation. SGAI Conf. Alexandros Gkiokas, Alexandra I. Cristea, Matthew Thorpe