Cikkek nyilvánosan hozzáférhető megbízással - S osherTovábbi információ
Sehol sem hozzáférhető: 9
A guide to the TV zoo
M Burger, ACG Mennucci, S Osher, M Rumpf, M Burger, S Osher
Level Set and PDE Based Reconstruction Methods in Imaging: Cetraro, Italy …, 2013
Megbízások: German Research Foundation
EM-TV methods for inverse problems with Poisson noise
M Burger, ACG Mennucci, S Osher, M Rumpf, A Sawatzky, C Brune, ...
Level Set and PDE Based Reconstruction Methods in Imaging: Cetraro, Italy …, 2013
Megbízások: German Research Foundation
Digitized PDE method for data restoration
S Osher, J Shen
Handbook of analytic computational methods in applied Mathematics, 751-771, 2019
Megbízások: US National Science Foundation
Task selection and collision-free route planning for mobile crowdsensing using multi-population mean-field games
Y Kang, S Liu, H Zhang, Z Han, S Osher, HV Poor
IEEE Transactions on Green Communications and Networking 5 (4), 1947-1960, 2021
Megbízások: US Department of Defense
Task selection and route planning for mobile crowd sensing using multi-population mean-field games
Y Kang, S Liu, H Zhang, Z Han, S Osher, HV Poor
ICC 2021-IEEE International Conference on Communications, 1-6, 2021
Megbízások: US Department of Defense
Partial differential equations for training deep neural networks
P Chaudhari, A Oberman, S Osher, S Soatto, G Carlier
2017 51st Asilomar Conference on Signals, Systems, and Computers, 1627-1631, 2017
Megbízások: US Department of Energy, US Department of Defense
Splitting enables overcoming the curse of dimensionality
J Darbon, SJ Osher
Splitting Methods in Communication, Imaging, Science, and Engineering, 427-432, 2016
Megbízások: US Department of Energy
RESIRE: Accurate tomography with real space iterative reconstruction
M Pham, Y Yuan, A Rana, S Osher, J Miao
Megbízások: US National Science Foundation, US Department of Energy
Soft x-ray vector ptycho-tomography: a new quantitative vector nanoimaging method for spin textures in 3D
CT Liao, A Rana, E Iacocca, J Zou, M Pham, X Lu, EEC Subramanian, ...
Spintronics XVI 12656, 258-260, 2023
Megbízások: US National Science Foundation, US Department of Energy
Valahol hozzáférhető: 169
Nonlocal operators with applications to image processing
G Gilboa, S Osher
Multiscale Modeling & Simulation 7 (3), 1005-1028, 2009
Megbízások: US National Institutes of Health
Bregmanized nonlocal regularization for deconvolution and sparse reconstruction
X Zhang, M Burger, X Bresson, S Osher
SIAM journal on imaging sciences 3 (3), 253-276, 2010
Megbízások: German Research Foundation
Geometric applications of the split Bregman method: segmentation and surface reconstruction
T Goldstein, X Bresson, S Osher
Journal of scientific computing 45, 272-293, 2010
Megbízások: US National Institutes of Health
Image super-resolution by TV-regularization and Bregman iteration
A Marquina, SJ Osher
Journal of Scientific Computing 37, 367-382, 2008
Megbízások: US National Institutes of Health
Kernel density estimation and intrinsic alignment for shape priors in level set segmentation
D Cremers, SJ Osher, S Soatto
International journal of computer vision 69, 335-351, 2006
Megbízások: German Research Foundation
A review of level-set methods and some recent applications
F Gibou, R Fedkiw, S Osher
Journal of Computational Physics 353, 82-109, 2018
Megbízások: US National Science Foundation, US Department of Energy, US Department of …
Fast linearized Bregman iteration for compressive sensing and sparse denoising
S Osher, Y Mao, B Dong, W Yin
Megbízások: US National Institutes of Health
A nonlinear inverse scale space method for a convex multiplicative noise model
J Shi, S Osher
SIAM Journal on imaging sciences 1 (3), 294-321, 2008
Megbízások: US National Institutes of Health
Determining the three-dimensional atomic structure of an amorphous solid
Y Yang, J Zhou, F Zhu, Y Yuan, DJ Chang, DS Kim, M Pham, A Rana, ...
Nature 592 (7852), 60-64, 2021
Megbízások: US National Science Foundation, US Department of Energy, US Department of …
Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM)
H Gao, H Yu, S Osher, G Wang
Inverse problems 27 (11), 115012, 2011
Megbízások: US National Institutes of Health
A machine learning framework for solving high-dimensional mean field game and mean field control problems
L Ruthotto, SJ Osher, W Li, L Nurbekyan, SW Fung
Proceedings of the National Academy of Sciences 117 (17), 9183-9193, 2020
Megbízások: US National Science Foundation, US Department of Defense
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