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Stanley Osher
Researcher at University of California, Los Angeles
Publications - 549
Citations - 112414
Stanley Osher is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Level set method & Computer science. The author has an hindex of 114, co-authored 510 publications receiving 104028 citations. Previous affiliations of Stanley Osher include University of Minnesota & University of Innsbruck.
Papers
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Journal ArticleDOI
Controlling propagation of epidemics via mean-field control
TL;DR: In this paper, a mean-field game model was introduced to control the propagation of epidemics in the COVID-19 pandemic, where the authors introduced a mean field game model in controlling epidemics.
Journal ArticleDOI
Efficient Characteristic Projection in Upwind Difference Schemes for Hyperbolic Systems
TL;DR: A complementary projection technique can be used to formulate upwind differencing without specifying a basis, and for systems with eigenvalues of high multiplicity, this approach simplifies the analytical and programming effort and reduces the computational cost.
Journal ArticleDOI
Iterative Total Variation Regularization with Non-Quadratic Fidelity
TL;DR: A generalized iterative regularization procedure based on the total variation penalization is introduced for image denoising models with non-quadratic convex fidelity terms to solve the issue of solvability of minimization problems arising in each step of the iterative procedure.
Book ChapterDOI
Wasserstein Proximal of GANs
TL;DR: In this paper, the Wasserstein-2 metric proximal is applied on the generators to define a parametrization invariant natural gradient by pulling back optimal transport structures from probability space to parameter space.
Proceedings ArticleDOI
Asymmetric and symmetric unbiased image registration: Statistical assessment of performance
TL;DR: An asymmetric version of a recently proposed unbiased registration method is investigated, using mutual information as the matching criterion, and it is demonstrated that the unbiased methods have higher reproducibility and less likely to detect changes in the absence of any real physiological change.