Image inpainting is an important research direction in the study of computer vision, and is
widely used in image editing and photo inpainting etc. Traditional image inpainting …

Recent work in machine learning shows that deep neural networks can be used to solve a
wide variety of inverse problems arising in computational imaging. We explore the central …

Reconstructing medical images from partial measurements is an important inverse problem
in Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Existing solutions …

Signal processing, communications, and control have traditionally relied on classical
statistical modeling techniques. Such model-based methods utilize mathematical …

Decision making algorithms are used in a multitude of different applications. Conventional
approaches for designing decision algorithms employ principled and simplified modelling …

We describe the new field of the mathematical analysis of deep learning. This field emerged
around a list of research questions that were not answered within the classical framework of …

Abstract Limited-Angle Computed Tomography (LACT) is a non-destructive 3D imaging
technique used in a variety of applications ranging from security to medicine. The limited …

Recent efforts on solving inverse problems in imaging via deep neural networks use
architectures inspired by a fixed number of iterations of an optimization method. The number …

Most compressive sensing (CS) reconstruction methods can be divided into two categories,
ie model-based methods and classical deep network methods. By unfolding the iterative …

Well-known compressed sensing (CS) is widely used in image acquisition and
reconstruction. However, accurately reconstructing images from measurements at low …