hp-VPINNs: Variational physics-informed neural networks with domain decomposition
We formulate a general framework for hp-variational physics-informed neural networks (hp-
VPINNs) based on the nonlinear approximation of shallow and deep neural networks and …
VPINNs) based on the nonlinear approximation of shallow and deep neural networks and …
Variational physics-informed neural networks for solving partial differential equations
Physics-informed neural networks (PINNs)[31] use automatic differentiation to solve partial
differential equations (PDEs) by penalizing the PDE in the loss function at a random set of …
differential equations (PDEs) by penalizing the PDE in the loss function at a random set of …
Nonlinear approximation via compositions
Given a function dictionary D and an approximation budget N∈ N, nonlinear approximation
seeks the linear combination of the best N terms {T n} 1≤ n≤ N⊆ D to approximate a given …
seeks the linear combination of the best N terms {T n} 1≤ n≤ N⊆ D to approximate a given …
Cardinality minimization, constraints, and regularization: a survey
We survey optimization problems that involve the cardinality of variable vectors in
constraints or the objective function. We provide a unified viewpoint on the general problem …
constraints or the objective function. We provide a unified viewpoint on the general problem …
Fast optical proximity correction method based on nonlinear compressive sensing
X Ma, Z Wang, Y Li, GR Arce, L Dong… - Optics Express, 2018 - opg.optica.org
Optical proximity correction (OPC) is an extensively used resolution enhancement technique
(RET) in optical lithography. To date, the computational efficiency has become a big issue …
(RET) in optical lithography. To date, the computational efficiency has become a big issue …
Non-linear inverse scattering via sparsity regularized contrast source inversion
Two compressive sensing inspired approaches for the solution of non-linear inverse
scattering problems are introduced and discussed. Differently from the sparsity promoting …
scattering problems are introduced and discussed. Differently from the sparsity promoting …
A non-linear reweighted total variation image reconstruction algorithm for electrical capacitance tomography
A new iterative image reconstruction algorithm for electrical capacitance tomography (ECT)
is proposed which is based on iterative soft thresholding of a total variation penalty and …
is proposed which is based on iterative soft thresholding of a total variation penalty and …
PPR: Plug-and-play regularization model for solving nonlinear imaging inverse problems
B Shi, Q Lian, X Fan - Signal Processing, 2019 - Elsevier
The problem of recovering an image of interest from nonlinear measured data is
challenging. To address this nonlinear imaging inverse problem, we propose a novel Plug …
challenging. To address this nonlinear imaging inverse problem, we propose a novel Plug …
[PDF][PDF] 基于压缩感知的快速激光超声合成孔径聚焦技术
何志同， 应恺宁， 戴鹭楠， 倪辰荫 - Chinese Journal of Lasers, 2024 - researching.cn
摘要传统激光超声合成孔径聚焦技术(LU-SAFT) 通常需要在待测样品表面以小步长扫描来提高
横向分辨率, 但小扫描步长会导致总检测时间过长, 影响检测效率. 针对这一问题 …
横向分辨率, 但小扫描步长会导致总检测时间过长, 影响检测效率. 针对这一问题 …