9 citations · 9 across the 3 of their papers we have counts for
4 papers
Linear Inverse Problems Using a Generative Compound Gaussian Prior
Carter Lyons, Raghu G. Raj, Margaret Cheney
Since most inverse problems arising in scientific and engineering applications are ill-posed, prior information about the solution space is incorporated, typically through regulari…
On Generalization Bounds for Deep Compound Gaussian Neural Networks
Carter Lyons, Raghu G. Raj, Margaret Cheney
Algorithm unfolding or unrolling is the technique of constructing a deep neural network (DNN) from an iterative algorithm. Unrolled DNNs often provide better interpretability and s…
Deep Regularized Compound Gaussian Network for Solving Linear Inverse Problems
Carter Lyons, Raghu G. Raj, Margaret Cheney
Incorporating prior information into inverse problems, e.g. via maximum-a-posteriori estimation, is an important technique for facilitating robust inverse problem solutions. In thi…
A Compound Gaussian Least Squares Algorithm and Unrolled Network for Linear Inverse Problems
Carter Lyons, Raghu G. Raj, Margaret Cheney
For solving linear inverse problems, particularly of the type that appears in tomographic imaging and compressive sensing, this paper develops two new approaches. The first approac…