Zobrazeno 1 - 10
of 891
pro vyhledávání: '"Osher, Stanley"'
Sampling from a target distribution is a fundamental problem. Traditional Markov chain Monte Carlo (MCMC) algorithms, such as the unadjusted Langevin algorithm (ULA), derived from the overdamped Langevin dynamics, have been extensively studied. From
Externí odkaz:
http://arxiv.org/abs/2410.08987
Classical neural ordinary differential equations (ODEs) are powerful tools for approximating the log-density functions in high-dimensional spaces along trajectories, where neural networks parameterize the velocity fields. This paper proposes a system
Externí odkaz:
http://arxiv.org/abs/2409.16471
In this work, we investigate the convergence properties of the backward regularized Wasserstein proximal (BRWP) method for sampling a target distribution. The BRWP approach can be shown as a semi-implicit time discretization for a probability flow OD
Externí odkaz:
http://arxiv.org/abs/2409.01567
Ptychography is a popular imaging technique that combines diffractive imaging with scanning microscopy. The technique consists of a coherent beam that is scanned across an object in a series of overlapping positions, leading to reliable and improved
Externí odkaz:
http://arxiv.org/abs/2408.03532
Autor:
Nguyen, Tan M., Nguyen, Tam, Ho, Nhat, Bertozzi, Andrea L., Baraniuk, Richard G., Osher, Stanley J.
Self-attention is key to the remarkable success of transformers in sequence modeling tasks including many applications in natural language processing and computer vision. Like neural network layers, these attention mechanisms are often developed by h
Externí odkaz:
http://arxiv.org/abs/2406.13781
We study approximations to the Moreau envelope -- and infimal convolutions more broadly -- based on Laplace's method, a classical tool in analysis which ties certain integrals to suprema of their integrands. We believe the connection between Laplace'
Externí odkaz:
http://arxiv.org/abs/2406.02003
Mean-field control (MFC) problems aim to find the optimal policy to control massive populations of interacting agents. These problems are crucial in areas such as economics, physics, and biology. We consider the non-local setting, where the interacti
Externí odkaz:
http://arxiv.org/abs/2405.10922
We develop a class of barycenter problems based on mean field control problems in three dimensions with associated reactive-diffusion systems of unnormalized multi-species densities. This problem is the generalization of the Wasserstein barycenter pr
Externí odkaz:
http://arxiv.org/abs/2404.01586
Optimal control problems are crucial in various domains, including path planning, robotics, and humanoid control, demonstrating their broad applicability. The connection between optimal control and Hamilton-Jacobi (HJ) partial differential equations
Externí odkaz:
http://arxiv.org/abs/2403.02468
Autor:
Manekar, Raunak, Negrini, Elisa, Pham, Minh, Jacobs, Daniel, Srivastava, Jaideep, Osher, Stanley J., Miao, Jianwei
Phase retrieval (PR) is fundamentally important in scientific imaging and is crucial for nanoscale techniques like coherent diffractive imaging (CDI). Low radiation dose imaging is essential for applications involving radiation-sensitive samples. How
Externí odkaz:
http://arxiv.org/abs/2402.17745