210 citations · 1.2k across the 58 of their papers we have counts for
62 papers
Fried deconvolution
Jerome Gilles, Stanley Osher
In this paper we present a new approach to deblur the effect of atmospheric turbulence in the case of long range imaging. Our method is based on an analytical formulation, the Frie…
Wavelet Burst Accumulation for turbulence mitigation
Jerome Gilles, Stanley Osher
In this paper, we investigate the extension of the recently proposed weighted Fourier burst accumulation (FBA) method into the wavelet domain. The purpose of FBA is to reconstruct…
A Hamilton-Jacobi-based Proximal Operator
Stanley Osher, Howard Heaton, Samy Wu Fung
First-order optimization algorithms are widely used today. Two standard building blocks in these algorithms are proximal operators (proximals) and gradients. Although gradients can…
How Does Momentum Benefit Deep Neural Networks Architecture Design? A Few Case Studies
Bao Wang, Hedi Xia, Tan Nguyen +1
We present and review an algorithmic and theoretical framework for improving neural network architecture design via momentum. As case studies, we consider how momentum can improve…
FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention
Tan M. Nguyen, Vai Suliafu, Stanley J. Osher +2
We propose FMMformers, a class of efficient and flexible transformers inspired by the celebrated fast multipole method (FMM) for accelerating interacting particle simulation. FMM d…
Wasserstein Proximal of GANs
Alex Tong Lin, Wuchen Li, Stanley Osher +1
We introduce a new method for training generative adversarial networks by applying the Wasserstein-2 metric proximal on the generators. The approach is based on Wasserstein informa…