Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Leon Bungert"'
Autor:
Leon Bungert, Matthias J. Ehrhardt
Publikováno v:
IEEE Access, Vol 8, Pp 222944-222955 (2020)
Multi-modality (or multi-channel) imaging is becoming increasingly important and more widely available, e.g. hyperspectral imaging in remote sensing, spectral CT in material sciences as well as multi-contrast MRI and PET-MR in medicine. Research in t
Externí odkaz:
https://doaj.org/article/8b1765e95ff246f8a5902776a45e08c8
Autor:
Leon Bungert
Publikováno v:
Advances in Continuous and Discrete Models. 2023
We investigate the limiting behavior of solutions to the inhomogeneous $p$-Laplacian equation $-\Delta_p u = \mu_p$ subject to Neumann boundary conditions. For right hand sides which are arbitrary signed measures we show that solutions converge to a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7acb109f00774dd977afbd466adbb07
https://doi.org/10.1186/s13662-023-03754-8
https://doi.org/10.1186/s13662-023-03754-8
Publikováno v:
IMA Journal of Numerical Analysis
Lipschitz learning is a graph-based semisupervised learning method where one extends labels from a labeled to an unlabeled data set by solving the infinity Laplace equation on a weighted graph. In this work we prove uniform convergence rates for solu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8899ec77b777f4ccd3cb3c49d98845e3
Autor:
Leon Bungert, Martin Burger
Publikováno v:
Numerical Control: Part A ISBN: 9780323850599
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::99a97470683fde3ab53cc9671fa86d82
https://doi.org/10.1016/bs.hna.2021.12.013
https://doi.org/10.1016/bs.hna.2021.12.013
Publikováno v:
SIAM Journal on Imaging Sciences
SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2021, 14 (3), pp.1114-1148
SIAM Journal on Imaging Sciences, 2021, 14 (3), pp.1114-1148. ⟨10.1137/20M1384154⟩
SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2021, 14 (3), pp.1114-1148
SIAM Journal on Imaging Sciences, 2021, 14 (3), pp.1114-1148. ⟨10.1137/20M1384154⟩
Neural networks have revolutionized the field of data science, yielding remarkable solutions in a data-driven manner. For instance, in the field of mathematical imaging, they have surpassed traditional methods based on convex regularization. However,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1daef9e37171fade8712985cf64121a
https://hal.archives-ouvertes.fr/hal-03323046
https://hal.archives-ouvertes.fr/hal-03323046
We establish an equivalence between a family of adversarial training problems for non-parametric binary classification and a family of regularized risk minimization problems where the regularizer is a nonlocal perimeter functional. The resulting regu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7b4382e73faac0044dfe7b4871ff752
Localization of Passive 3-D Coils as an Inverse Problem: Theoretical Analysis and a Numerical Method
This article provides both a theoretical analysis and a numerical method for the inverse source problem of locating multiple passive 3-D coils based on measurements of their superposed magnetic fields. In our context, a 3-D coil consists of three con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fc3c79c20a614a322e760291773e820
https://publica.fraunhofer.de/handle/publica/263492
https://publica.fraunhofer.de/handle/publica/263492
Publikováno v:
Pure and Applied Analysis
Pure Appl. Anal. 2, no. 3 (2020), 703-738
Bungert, L, Korolev, Y & Burger, M 2020, ' Structural analysis of an L-infinity variational problem and relations to distance functions ', Pure and Applied Analysis, vol. 2, no. 3, pp. 703-738 . https://doi.org/10.2140/paa.2020.2.703
Pure Appl. Anal. 2, no. 3 (2020), 703-738
Bungert, L, Korolev, Y & Burger, M 2020, ' Structural analysis of an L-infinity variational problem and relations to distance functions ', Pure and Applied Analysis, vol. 2, no. 3, pp. 703-738 . https://doi.org/10.2140/paa.2020.2.703
In this work we analyse the functional ${\cal J}(u)=\|\nabla u\|_\infty$ defined on Lipschitz functions with homogeneous Dirichlet boundary conditions. Our analysis is performed directly on the functional without the need to approximate with smooth $
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c66ff17480e876341566a6498e25703d
Publikováno v:
Computing and Visualization in Science. 18:193-202
Based on the local discontinuous Galerkin method, two substantially different mixed formulations for the subjective surfaces problem are compared using a number of numerical tests of various types. The work also performs the energy stability analysis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a4a35633c616dcf116aefb9169a9f930
https://doi.org/10.1007/s00791-018-0291-4
https://doi.org/10.1007/s00791-018-0291-4
Publikováno v:
Journal of Mathematical Imaging and Vision. 58:147-161
The work formulates and evaluates the local discontinuous Galerkin method for the subjective surfaces problem based on the curvature driven level set equation. A new mixed formulation simplifying the treatment of nonlinearities is proposed. The numer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e82170a824c881e1b71a25d70caea19d
https://doi.org/10.1007/s10851-016-0695-z
https://doi.org/10.1007/s10851-016-0695-z