4 papers
Solving Convolution-type Integral Equations using Preconditioned Neural Operators
Raymond Chan, Lingfeng Li
Convolution-type integral equations arise from various fields, \textit{e.g.}, finite impulse response filters in signal processing and deblurring problems in image processing. When…
A level-wise training scheme for learning neural multigrid smoothers with application to integral equations
Lingfeng Li, Yin King Chu, Raymond Chan +1
Convolution-type integral equations commonly occur in signal processing and image processing. Discretizing these equations yields large and ill-conditioned linear systems. While th…
TRIDENT: The Nonlinear Trilogy for Implicit Neural Representations
Zhenda Shen, Yanqi Cheng, Raymond H. Chan +3
Implicit neural representations (INRs) have garnered significant interest recently for their ability to model complex, high-dimensional data without explicit parameterisation. In t…
Single-Shot Plug-and-Play Methods for Inverse Problems
Yanqi Cheng, Lipei Zhang, Zhenda Shen +5
The utilisation of Plug-and-Play (PnP) priors in inverse problems has become increasingly prominent in recent years. This preference is based on the mathematical equivalence betwee…