Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Dejan Slepčev"'
Publikováno v:
Oberwolfach Reports. 17:1391-1467
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f94589377282dc20c1e3a4c130b9b62
https://doi.org/10.4171/owr/2020/29
https://doi.org/10.4171/owr/2020/29
Publikováno v:
Journal of Scientific Computing. 92
We investigate identifying the boundary of a domain from sample points in the domain. We introduce new estimators for the normal vector to the boundary, distance of a point to the boundary, and a test for whether a point lies within a boundary strip.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6577a633de72638ef44cf018f5e794d5
https://doi.org/10.1007/s10915-022-01894-9
https://doi.org/10.1007/s10915-022-01894-9
Publikováno v:
Nonlinearity
Nonlinearity, IOP Publishing, 2020, 33 (8), pp.3846--3888. ⟨10.1088/1361-6544/ab81ee⟩
Nonlinearity, IOP Publishing, 2020, 33 (8), pp.3846--3888. ⟨10.1088/1361-6544/ab81ee⟩
International audience; We consider adaptations of the Mumford-Shah functional to graphs. These are based on discretizations of nonlocal approximations to the Mumford-Shah functional. Motivated by applications in machine learning we study the random
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6be032e0a9569947e82077200a2d9855
https://doi.org/10.1088/1361-6544/ab81ee
https://doi.org/10.1088/1361-6544/ab81ee
Publikováno v:
Active Particles, Volume 3 ISBN: 9783030933012
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d346731194053ae7255bf68df1bcbf9e
https://doi.org/10.1007/978-3-030-93302-9_4
https://doi.org/10.1007/978-3-030-93302-9_4
Publikováno v:
Foundations of Computational Mathematics. 20:827-887
We study the convergence of the graph Laplacian of a random geometric graph generated by an i.i.d. sample from a m-dimensional submanifold $${\mathcal {M}}$$ in $$\mathbb {R}^d$$ as the sample size n increases and the neighborhood size h tends to zer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f725a24fdcdd7caae0d9058ce02a0d0
https://doi.org/10.1007/s10208-019-09436-w
https://doi.org/10.1007/s10208-019-09436-w
Autor:
Francesco S. Patacchini, Dejan Slepčev
We study the approximation of the nonlocal-interaction equation restricted to a compact manifold $\mathcal{M}$ embedded in $\mathbb{R}^d$, and more generally compact sets with positive reach (i.e. prox-regular sets). We show that the equation on $\ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::776f320aa29180198d694c4ca4773d8b
Publikováno v:
Advances in Applied Probability. 49:1067-1090
We investigate the estimation of the perimeter of a set by a graph cut of a random geometric graph. For Ω ⊆ D = (0, 1)d with d ≥ 2, we are given n random independent and identically distributed points on D whose membership in Ω is known. We con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a99dd539a7702f27e9db47d5cc6ba5e3
https://doi.org/10.1017/apr.2017.34
https://doi.org/10.1017/apr.2017.34
Autor:
Dejan Slepčev, Xin Yang Lu
Publikováno v:
ESAIM: Control, Optimisation and Calculus of Variations. 27:8
We propose a model for finding one-dimensional structure in a given measure. Our approach is based on minimizing an objective functional which combines the average-distance functional to measure the quality of the approximation and penalizes the curv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a156098f2deeaad1ee33271299dda70
https://doi.org/10.1051/cocv/2021002
https://doi.org/10.1051/cocv/2021002
Publikováno v:
Journal of mathematical imaging and vision. 59(2)
Transport based distances, such as the Wasserstein distance and earth mover'sdistance, have been shown to be an effective tool in signal and image analysis. The success of transport based distances is in part due to their Lagrangian nature which allo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::2ad0fffe5f7751ce5aa5a683c71c4a31
https://pubmed.ncbi.nlm.nih.gov/30233108
https://pubmed.ncbi.nlm.nih.gov/30233108
Publikováno v:
Kolouri, S, Park, S, Thorpe, M, Rohde, G & Slepcev, D 2017, ' Optimal Mass Transport: Signal processing and machine-learning applications ', IEEE Signal Processing Magazine, vol. 34, no. 4, pp. 43-59 . https://doi.org/10.1109/MSP.2017.2695801
Transport-based techniques for signal and data analysis have received increased attention recently. Given their ability to provide accurate generative models for signal intensities and other data distributions, they have been used in a variety of app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db10faacd66700c5e3a305c3eaf7afe2
https://pubmed.ncbi.nlm.nih.gov/29962824
https://pubmed.ncbi.nlm.nih.gov/29962824