default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMatthew Thorpe
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[j9]Oliver M. Crook, Mihai Cucuringu, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis:
A linear transportation Lp distance for pattern recognition. Pattern Recognit. 147: 110080 (2024)- [j8]Adrien Weihs, Matthew Thorpe:
Consistency of Fractional Graph-Laplacian Regularization in Semisupervised Learning with Finite Labels. SIAM J. Math. Anal. 56(4): 4253-4295 (2024) - 2023
- [j7]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:
Navigating the development challenges in creating complex data systems. Nat. Mac. Intell. 5(7): 681-686 (2023) - [c6]Yikun Bai, Bernhard Schmitzer, Matthew Thorpe, Soheil Kolouri:
Sliced Optimal Partial Transport. CVPR 2023: 13681-13690 - [i18]Xinran Liu, Yikun Bai, Huy Tran, Zhanqi Zhu, Matthew Thorpe, Soheil Kolouri:
PTLp: Partial Transport Lp Distances. CoRR abs/2307.13571 (2023) - [i17]Adrien Weihs, Jalal Fadili, Matthew Thorpe:
Discrete-to-Continuum Rates of Convergence for $p$-Laplacian Regularization. CoRR abs/2310.12691 (2023) - [i16]Keaton Hamm, Caroline Moosmüller, Bernhard Schmitzer, Matthew Thorpe:
Manifold learning in Wasserstein space. CoRR abs/2311.08549 (2023) - 2022
- [j6]Tianji Cai, Junyi Cheng, Bernhard Schmitzer, Matthew Thorpe:
The Linearized Hellinger-Kantorovich Distance. SIAM J. Imaging Sci. 15(1): 45-83 (2022) - [c5]Matthew Thorpe, Tan Minh Nguyen, Hedi Xia, Thomas Strohmer, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang:
GRAND++: Graph Neural Diffusion with A Source Term. ICLR 2022 - [i15]Irene Fonseca, Lisa Maria Kreusser, Carola-Bibiane Schönlieb, Matthew Thorpe:
Γ-Convergence of an Ambrosio-Tortorelli approximation scheme for image segmentation. CoRR abs/2202.04965 (2022) - [i14]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:
Classification of datasets with imputed missing values: does imputation quality matter? CoRR abs/2206.08478 (2022) - [i13]Nicolás García Trillos, Ryan Murray, Matthew Thorpe:
Rates of Convergence for Regression with the Graph Poly-Laplacian. CoRR abs/2209.02305 (2022) - [i12]Yikun Bai, Bernhard Schmitzer, Matthew Thorpe, Soheil Kolouri:
Sliced Optimal Partial Transport. CoRR abs/2212.08049 (2022) - 2021
- [j5]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:
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nat. Mach. Intell. 3(3): 199-217 (2021) - [c4]Matthew Thorpe, Bao Wang:
Robust Certification for Laplace Learning on Geometric Graphs. MSML 2021: 896-920 - [i11]Matthew Thorpe, Bao Wang:
Robust Certification for Laplace Learning on Geometric Graphs. CoRR abs/2104.10837 (2021) - 2020
- [c3]Jeff Calder, Brendan Cook, Matthew Thorpe, Dejan Slepcev:
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates. ICML 2020: 1306-1316 - [i10]Nicolás García Trillos, Ryan Murray, Matthew Thorpe:
From graph cuts to isoperimetric inequalities: Convergence rates of Cheeger cuts on data clouds. CoRR abs/2004.09304 (2020) - [i9]Jeff Calder, Dejan Slepcev, Matthew Thorpe:
Rates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates. CoRR abs/2006.02765 (2020) - [i8]Jeff Calder, Brendan Cook, Matthew Thorpe, Dejan Slepcev:
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates. CoRR abs/2006.11184 (2020) - [i7]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:
Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review. CoRR abs/2008.06388 (2020) - [i6]Oliver M. Crook, Mihai Cucuringu, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis:
A Linear Transportation Lp Distance for Pattern Recognition. CoRR abs/2009.11262 (2020)
2010 – 2019
- 2019
- [j4]Dejan Slepcev, Matthew Thorpe:
Analysis of p-Laplacian Regularization in Semisupervised Learning. SIAM J. Math. Anal. 51(3): 2085-2120 (2019) - [i5]Oliver M. Crook, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis:
PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds. CoRR abs/1909.10221 (2019) - 2018
- [c2]Serim Park, Matthew Thorpe:
Representing and Learning High Dimensional Data With the Optimal Transport Map From a Probabilistic Viewpoint. CVPR 2018: 7864-7872 - [i4]Matthew M. Dunlop, Dejan Slepcev, Andrew M. Stuart, Matthew Thorpe:
Large Data and Zero Noise Limits of Graph-Based Semi-Supervised Learning Algorithms. CoRR abs/1805.09450 (2018) - 2017
- [j3]Matthew Thorpe, Serim Park, Soheil Kolouri, Gustavo K. Rohde, Dejan Slepcev:
A Transportation Lp Distance for Signal Analysis. J. Math. Imaging Vis. 59(2): 187-210 (2017) - [j2]Soheil Kolouri, Se Rim Park, Matthew Thorpe, Dejan Slepcev, Gustavo K. Rohde:
Optimal Mass Transport: Signal processing and machine-learning applications. IEEE Signal Process. Mag. 34(4): 43-59 (2017) - [i3]Dejan Slepcev, Matthew Thorpe:
Analysis of $p$-Laplacian Regularization in Semi-Supervised Learning. CoRR abs/1707.06213 (2017) - 2016
- [i2]Soheil Kolouri, Serim Park, Matthew Thorpe, Dejan Slepcev, Gustavo K. Rohde:
Transport-based analysis, modeling, and learning from signal and data distributions. CoRR abs/1609.04767 (2016) - [i1]Matthew Thorpe, Serim Park, Soheil Kolouri, Gustavo K. Rohde, Dejan Slepcev:
A Transportation Lp Distance for Signal Analysis. CoRR abs/1609.08669 (2016) - 2015
- [j1]Matthew Thorpe, Florian Theil, Adam M. Johansen, Neil Cade:
Convergence of the k-Means Minimization Problem using Γ-Convergence. SIAM J. Appl. Math. 75(6): 2444-2474 (2015) - 2014
- [c1]Alexandros Gkiokas, Alexandra I. Cristea, Matthew Thorpe:
Self-reinforced Meta Learning for Belief Generation. SGAI Conf. 2014: 185-190
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 22:06 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
