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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
Unbalanced and Partial $$L_1$$L1 Monge---Kantorovich Problem: A Scalable Parallel First-Order Method
TL;DR: This work proposes a new algorithm to solve the unbalanced and partial $$L_1$$L1-Monge–Kantorovich problems that is scalable and parallel, conceptually simple, computationally cheap, and easy to parallelize.
Journal ArticleDOI
Joint Sensing Task Assignment and Collision-Free Trajectory Optimization for Mobile Vehicle Networks Using Mean-Field Games
TL;DR: In this paper, a mean-field-game (MFG) algorithm was proposed to solve the problem of joint task assignment and collision-free trajectory optimization for mobile robots. But the complexity of the algorithm is linear with the total number of grid points in the proposed MFG problem.
Patent
Apparatus and method for surface capturing and volumetric analysis of multidimensional images
TL;DR: In this paper, a method and apparatus for volumetric image analysis and processing is described, which is able to obtain geometrical information from multi-dimensional (3D or more) images.
Posted Content
Fast Algorithms for Earth Mover's Distance Based on Optimal Transport and L1 Type Regularization I
TL;DR: A primal-dual algorithm to approximate the Earth Mover's distance is proposed, which uses very simple updates at each iteration and is shown to converge very rapidly.
Proceedings ArticleDOI
Level set and PDE methods for computer graphics
TL;DR: This course begins with preparatory material that introduces the concept of using partial differential equations to solve problems in computer graphics, geometric modeling and computer vision, and describes the structure and behavior of several different types of differential equations.