3 papers
eess.SP2024
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…
eess.SP2024
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…
stat.ML2024
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…