Dejan Slepčev

2.6k total citations
43 papers, 1.3k citations indexed

About

Dejan Slepčev is a scholar working on Applied Mathematics, Computational Theory and Mathematics and Computational Mechanics. According to data from OpenAlex, Dejan Slepčev has authored 43 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Applied Mathematics, 17 papers in Computational Theory and Mathematics and 11 papers in Computational Mechanics. Recurrent topics in Dejan Slepčev's work include Advanced Mathematical Modeling in Engineering (12 papers), Nonlinear Partial Differential Equations (12 papers) and Geometric Analysis and Curvature Flows (11 papers). Dejan Slepčev is often cited by papers focused on Advanced Mathematical Modeling in Engineering (12 papers), Nonlinear Partial Differential Equations (12 papers) and Geometric Analysis and Curvature Flows (11 papers). Dejan Slepčev collaborates with scholars based in United States, Canada and Italy. Dejan Slepčev's co-authors include Gustavo K. Rohde, Nicolás García Trillos, José A. Carrillo, Matthew Thorpe, Soheil Kolouri, Thomas Laurent, Marco Di Francesco, Alessio Figalli, Wei Wang and John A. Ozolek and has published in prestigious journals such as IEEE Transactions on Medical Imaging, ACM Transactions on Graphics and International Journal of Computer Vision.

In The Last Decade

Dejan Slepčev

42 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dejan Slepčev United States 19 380 276 228 221 162 43 1.3k
Filippo Santambrogio France 18 1.1k 2.8× 488 1.8× 174 0.8× 195 0.9× 387 2.4× 90 2.1k
Adam M. Oberman Canada 20 526 1.4× 405 1.5× 355 1.6× 161 0.7× 182 1.1× 45 1.3k
Dario Benedetto Italy 15 308 0.8× 138 0.5× 185 0.8× 109 0.5× 132 0.8× 46 923
Steve Abbott United States 10 371 1.0× 368 1.3× 240 1.1× 107 0.5× 278 1.7× 49 1.3k
М. К. Керимов Russia 17 401 1.1× 366 1.3× 167 0.7× 91 0.4× 268 1.7× 90 1.8k
J. C. Mason United Kingdom 12 311 0.8× 178 0.6× 161 0.7× 248 1.1× 66 0.4× 42 1.3k
Denis Talay France 24 246 0.6× 303 1.1× 301 1.3× 246 1.1× 389 2.4× 64 2.6k
Jean‐David Benamou France 22 850 2.2× 377 1.4× 600 2.6× 107 0.5× 281 1.7× 50 2.4k
Javier Segura Spain 19 572 1.5× 257 0.9× 83 0.4× 223 1.0× 72 0.4× 126 1.6k

Countries citing papers authored by Dejan Slepčev

Since Specialization
Citations

This map shows the geographic impact of Dejan Slepčev's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dejan Slepčev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dejan Slepčev more than expected).

Fields of papers citing papers by Dejan Slepčev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dejan Slepčev. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dejan Slepčev. The network helps show where Dejan Slepčev may publish in the future.

Co-authorship network of co-authors of Dejan Slepčev

This figure shows the co-authorship network connecting the top 25 collaborators of Dejan Slepčev. A scholar is included among the top collaborators of Dejan Slepčev based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dejan Slepčev. Dejan Slepčev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lu, Yulong, Dejan Slepčev, & Lihan Wang. (2023). Birth–death dynamics for sampling: global convergence, approximations and their asymptotics. Nonlinearity. 36(11). 5731–5772. 5 indexed citations
2.
Han, Ruiyu, Dejan Slepčev, & Yunan Yang. (2023). HV geometry for signal comparison. Quarterly of Applied Mathematics. 82(2). 391–430.
3.
Calder, Jeff, Dejan Slepčev, & Matthew Thorpe. (2023). Rates of convergence for Laplacian semi-supervised learning with low labeling rates. Research in the Mathematical Sciences. 10(1). 7 indexed citations
4.
Liu, Jian‐Guo, Robert L. Pego, & Dejan Slepčev. (2019). Least action principles for incompressible flows and geodesics between shapes. Calculus of Variations and Partial Differential Equations. 58(5). 5 indexed citations
5.
Thorpe, Matthew, et al.. (2017). A Transportation $$L^p$$ Distance for Signal Analysis. Journal of Mathematical Imaging and Vision. 59(2). 187–210. 30 indexed citations
6.
Trillos, Nicolás García, et al.. (2016). Consistency of cheeger and ratio graph cuts. Journal of Machine Learning Research. 17(1). 6268–6313. 24 indexed citations
7.
Liu, Jian‐Guo, Robert L. Pego, & Dejan Slepčev. (2016). Euler sprays and Wasserstein geometry of the space of shapes. arXiv (Cornell University). 1 indexed citations
8.
Lü, Xin & Dejan Slepčev. (2015). Average-distance problem for parameterized curves. ESAIM Control Optimisation and Calculus of Variations. 22(2). 404–416. 1 indexed citations
9.
Slepčev, Dejan, et al.. (2014). Mean-Curvature Flow of Voronoi Diagrams. Journal of Nonlinear Science. 25(1). 59–85. 1 indexed citations
10.
Trillos, Nicolás García & Dejan Slepčev. (2014). On the Rate of Convergence of Empirical Measures in ∞-transportation Distance. Canadian Journal of Mathematics. 67(6). 1358–1383. 44 indexed citations
11.
Wang, Wei, Dejan Slepčev, Saurav Basu, John A. Ozolek, & Gustavo K. Rohde. (2012). A Linear Optimal Transportation Framework for Quantifying and Visualizing Variations in Sets of Images. International Journal of Computer Vision. 101(2). 254–269. 98 indexed citations
12.
Carrillo, José A., Marco Di Francesco, Alessio Figalli, Thomas Laurent, & Dejan Slepčev. (2011). Global-in-time weak measure solutions and finite-time aggregation for nonlocal interaction equations. Duke Mathematical Journal. 156(2). 167 indexed citations
13.
Wang, Wei, John A. Ozolek, Dejan Slepčev, et al.. (2010). An Optimal Transportation Approach for Nuclear Structure-Based Pathology. IEEE Transactions on Medical Imaging. 30(3). 621–631. 58 indexed citations
14.
Slepčev, Dejan. (2009). Linear stability of selfsimilar solutions of unstable thin-film equations. Interfaces and Free Boundaries Mathematical Analysis Computation and Applications. 11(3). 375–398. 10 indexed citations
15.
Carrillo, José A., Stefano Lisini, Giuseppe Savaré, & Dejan Slepčev. (2009). Nonlinear mobility continuity equations and generalized displacement convexity. Journal of Functional Analysis. 258(4). 1273–1309. 59 indexed citations
16.
Slepčev, Dejan. (2008). Coarsening in Nonlocal Interfacial Systems. SIAM Journal on Mathematical Analysis. 40(3). 1029–1048. 16 indexed citations
17.
Otto, Félix, et al.. (2006). Coarsening Rates for a Droplet Model: Rigorous Upper Bounds. SIAM Journal on Mathematical Analysis. 38(2). 503–529. 44 indexed citations
18.
McCann, Robert J. & Dejan Slepčev. (2006). Second-order asymptotics for the fast-diffusion equation. International Mathematics Research Notices. 14 indexed citations
19.
Lio, Francesca Da, et al.. (2004). Nonlocal front propagation problems in bounded domains with Neumann‐type boundary conditions and applications. Asymptotic Analysis. 37(3-4). 257–292. 8 indexed citations
20.
Slepčev, Dejan. (2003). On level-set approach to motion of manifolds of arbitrary codimension. Interfaces and Free Boundaries Mathematical Analysis Computation and Applications. 5(4). 417–458. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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