Dejan Slepčev

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Gustavo Kunde RohdeUniversity of VirginiaVerified email at virginia.edu
Nicolás García TrillosAssociate Professor, Department of Statistics, University of Wisconsin-MadisonVerified email at wisc.edu
Matthew ThorpeAssociate Professor in Statistics, University of WarwickVerified email at warwick.ac.uk
José Antonio CarrilloUniversity of OxfordVerified email at maths.ox.ac.uk
Soheil KolouriComputer Science, Vanderbilt University, Nashville, TNVerified email at vanderbilt.edu
Thomas LaurentProfessor of Mathematics, Loyola Marymount UniversityVerified email at lmu.edu
Jeff CalderAssociate Professor, University of MinnesotaVerified email at umn.edu
Alessio FigalliETH ZurichVerified email at math.ethz.ch
Matthias HeinProfessor of Computer Science, University of TübingenVerified email at uni-tuebingen.de
Saurav BasuReseach Scientist, IBM ResearchVerified email at in.ibm.com
James von BrechtAssistant ProfessorVerified email at csulb.edu
Ann B. LeeDepartment of Statistics & Data Science and the Machine Learning Department, Carnegie MellonVerified email at cmu.edu
Xavier BressonAssoc Prof of Computer Science, NUS & Distinguished Researcher at Element IncVerified email at nus.edu.sg
Andrew M StuartComputing + Mathematical Sciences, CaltechVerified email at caltech.edu
Matthew DunlopGambit ResearchVerified email at nyu.edu
Ihsan TopalogluVirginia Commonwealth UniversityVerified email at vcu.edu
Andrea BertozziProf. of Math. and Mech. & Aero. Eng., Betsy Wood Knapp Chair for Innovation and Creativity, UCLAVerified email at math.ucla.edu
Robert PegoCarnegie Mellon UniversityVerified email at cmu.edu
Giuseppe SavaréProfessor of Mathematical Analysis, Department of Decisoion Sciences, Bocconi UniversityVerified email at unibocconi.it
Stefano LisiniRicercatore universitario, Università degli Studi di PaviaVerified email at unipv.it

Dejan Slepčev

Professor of Mathematical Sciences, Carnegie Mellon University

Verified email at math.cmu.edu - Homepage

applied analysis machine learning partial differential equations


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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	524	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	335	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	219	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	200*	2020
Continuum limit of total variation on point clouds N García Trillos, D Slepčev Archive for rational mechanics and analysis 220, 193-241, 2016	156	2016
A variational approach to the consistency of spectral clustering NG Trillos, D Slepčev Applied and Computational Harmonic Analysis 45 (2), 239-281, 2018	142	2018
Analysis of -Laplacian Regularization in Semisupervised Learning D Slepcev, M Thorpe SIAM Journal on Mathematical Analysis 51 (3), 2085-2120, 2019	137	2019
On the rate of convergence of empirical measures in -transportation distance N García Trillos, D Slepčev Canadian Journal of Mathematics 67, 1358-1383, 2015	119	2015
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	104	2010
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	100	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	99	2016
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	98	2020
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	97	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	84	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	63	2015
Properly-weighted graph Laplacian for semi-supervised learning J Calder, D Slepčev Applied mathematics & optimization 82, 1111-1159, 2020	60	2020
Optimal cone singularities for conformal flattening Y Soliman, D Slepčev, K Crane ACM Transactions on Graphics (TOG) 37 (4), 1-17, 2018	59	2018
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	58	2020
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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