Dejan Slepčev

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Gustavo Kunde RohdeUniversity of VirginiaGeverifieerd e-mailadres voor virginia.edu
Nicolás García TrillosAssociate Professor, Department of Statistics, University of Wisconsin-MadisonGeverifieerd e-mailadres voor wisc.edu
Matthew ThorpeAssociate Professor in Statistics, University of WarwickGeverifieerd e-mailadres voor warwick.ac.uk
José Antonio CarrilloUniversity of OxfordGeverifieerd e-mailadres voor maths.ox.ac.uk
Soheil KolouriComputer Science, Vanderbilt University, Nashville, TNGeverifieerd e-mailadres voor vanderbilt.edu
Thomas LaurentProfessor of Mathematics, Loyola Marymount UniversityGeverifieerd e-mailadres voor lmu.edu
Jeff CalderAssociate Professor, University of MinnesotaGeverifieerd e-mailadres voor umn.edu
Matthias HeinProfessor of Computer Science, University of TübingenGeverifieerd e-mailadres voor uni-tuebingen.de
Alessio FigalliETH ZurichGeverifieerd e-mailadres voor math.ethz.ch
Saurav BasuReseach Scientist, IBM ResearchGeverifieerd e-mailadres voor in.ibm.com
James von BrechtAssistant ProfessorGeverifieerd e-mailadres voor csulb.edu
Ann B. LeeDepartment of Statistics & Data Science and the Machine Learning Department, Carnegie MellonGeverifieerd e-mailadres voor cmu.edu
Xavier BressonAssoc Prof of Computer Science, NUS & Distinguished Researcher at Element IncGeverifieerd e-mailadres voor nus.edu.sg
Andrew M StuartComputing + Mathematical Sciences, CaltechGeverifieerd e-mailadres voor caltech.edu
Matthew DunlopGambit ResearchGeverifieerd e-mailadres voor nyu.edu
Ihsan TopalogluVirginia Commonwealth UniversityGeverifieerd e-mailadres voor vcu.edu
Giuseppe SavaréProfessor of Mathematical Analysis, Department of Decisoion Sciences, Bocconi UniversityGeverifieerd e-mailadres voor unibocconi.it
Stefano LisiniRicercatore universitario, Università degli Studi di PaviaGeverifieerd e-mailadres voor unipv.it
Robert PegoCarnegie Mellon UniversityGeverifieerd e-mailadres voor cmu.edu
Andrea BertozziProf. of Math. and Mech. & Aero. Eng., Betsy Wood Knapp Chair for Innovation and Creativity, UCLAGeverifieerd e-mailadres voor math.ucla.edu

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Dejan Slepčev

Professor of Mathematical Sciences, Carnegie Mellon University

Geverifieerd e-mailadres voor math.cmu.edu - Homepage

applied analysis machine learning partial differential equations


Titel Sorteren op citaties Sorteren op jaar Sorteren op titel	Geciteerd door Geciteerd door	Jaar
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	563	2017
Global-in-time weak measure solutions and finite-time aggregation for nonlocal interaction equations JA Carrillo, M DiFrancesco, A Figalli, T Laurent, D Slepčev Duke Math. J. 156 (2), 229-271, 2011	345	2011
A linear optimal transportation framework for quantifying and visualizing variations in sets of images W Wang, D Slepčev, S Basu, JA Ozolek, GK Rohde International journal of computer vision 101, 254-269, 2013	241	2013
Error estimates for spectral convergence of the graph Laplacian on random geometric graphs toward the Laplace–Beltrami operator N García Trillos, M Gerlach, M Hein, D Slepčev Foundations of Computational Mathematics 20 (4), 827-887, 2020	211*	2020
Continuum limit of total variation on point clouds N García Trillos, D Slepčev Archive for rational mechanics and analysis 220, 193-241, 2016	171	2016
Analysis of -Laplacian Regularization in Semisupervised Learning D Slepcev, M Thorpe SIAM Journal on Mathematical Analysis 51 (3), 2085-2120, 2019	152	2019
A variational approach to the consistency of spectral clustering NG Trillos, D Slepčev Applied and Computational Harmonic Analysis 45 (2), 239-281, 2018	148	2018
On the rate of convergence of empirical measures in -transportation distance N García Trillos, D Slepčev Canadian Journal of Mathematics 67, 1358-1383, 2015	122	2015
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	110	2020
Nonlinear mobility continuity equations and generalized displacement convexity JA Carrillo, S Lisini, G Savaré, D Slepčev Journal of Functional Analysis 258 (4), 1273-1309, 2010	110	2010
Consistency of cheeger and ratio graph cuts NG Trillos, D Slepčev, J Von Brecht, T Laurent, X Bresson The Journal of Machine Learning Research 17 (1), 6268-6313, 2016	105	2016
Existence and uniqueness of solutions to an aggregation equation with degenerate diffusion AL Bertozzi, D Slepcev Communications on Pure and Applied Analysis 9 (6), 1617-1637, 2010	105	2010
An optimal transportation approach for nuclear structure-based pathology W Wang, JA Ozolek, D Slepčev, AB Lee, C Chen, GK Rohde IEEE transactions on medical imaging 30 (3), 621-631, 2010	99	2010
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	87	2017
Coarsening rates for a droplet model: rigorous upper bounds F Otto, T Rump, D Slepcev SIAM journal on mathematical analysis 38 (2), 503-529, 2006	74	2006
Existence of ground states of nonlocal-interaction energies R Simione, D Slepčev, I Topaloglu Journal of Statistical Physics 159 (4), 972-986, 2015	69	2015
Properly-weighted graph Laplacian for semi-supervised learning J Calder, D Slepčev Applied mathematics & optimization 82, 1111-1159, 2020	66	2020
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	64	2020
Optimal cone singularities for conformal flattening Y Soliman, D Slepčev, K Crane ACM Transactions on Graphics (TOG) 37 (4), 1-17, 2018	63	2018
Ostwald ripening of droplets: the role of migration K Glasner, F Otto, T Rump, D Slepčev European journal of applied mathematics 20 (1), 1-67, 2009	55	2009

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