293 citations · 1.8k across the 110 of their papers we have counts for
10 papers · 1 filter
An Educated Warm Start For Deep Image Prior-Based Micro CT Reconstruction
Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt +4
Deep image prior (DIP) was recently introduced as an effective unsupervised approach for image restoration tasks. DIP represents the image to be recovered as the output of a deep c…
Conditional Variational Autoencoder for Learned Image Reconstruction
Chen Zhang, Riccardo Barbano, Bangti Jin
Learned image reconstruction techniques using deep neural networks have recently gained popularity, and have delivered promising empirical results. However, most approaches focus o…
Recovery of a Space-Time Dependent Diffusion Coefficient in Subdiffusion: Stability, Approximation and Error Analysis
Bangti Jin, Zhi Zhou
In this work, we study an inverse problem of recovering a space-time dependent diffusion coefficient in the subdiffusion model from the distributed observation, where the mathemati…
An Analysis of Stochastic Variance Reduced Gradient for Linear Inverse Problems
Bangti Jin, Zehui Zhou, Jun Zou
Stochastic variance reduced gradient (SVRG) is a popular variance reduction technique for accelerating stochastic gradient descent (SGD). We provide a first analysis of the method…
Unsupervised Knowledge-Transfer for Learned Image Reconstruction
Riccardo Barbano, Zeljko Kereta, Andreas Hauptmann +2
Deep learning-based image reconstruction approaches have demonstrated impressive empirical performance in many imaging modalities. These approaches usually require a large amount o…
Stochastic EM methods with Variance Reduction for Penalised PET Reconstructions
Zeljko Kereta, Robert Twyman, Simon Arridge +2
Expectation-maximization (EM) is a popular and well-established method for image reconstruction in positron emission tomography (PET) but it often suffers from slow convergence. Or…
Recovering Multiple Fractional Orders in Time-Fractional Diffusion in an Unknown Medium
Bangti Jin, Yavar Kian
In this work, we investigate an inverse problem of recovering multiple orders in a time-fractional diffusion model from the data observed at one single point on the boundary. We pr…
Recovering the Potential and Order in One-Dimensional Time-Fractional Diffusion with Unknown Initial Condition and Source
Bangti Jin, Zhi Zhou
This paper is concerned with an inverse problem of recovering a potential term and fractional order in a one-dimensional subdiffusion problem, which involves a Djrbashian-Caputo fr…
Reconstruction of a Space-Time Dependent Source in Subdiffusion Models via a Perturbation Approach
Bangti Jin, Yavar Kian, Zhi Zhou
In this article we study inverse problems of recovering a space-time dependent source component from the lateral boundary observation in a subidffusion model. The mathematical mode…
Recovery of the Order of Derivation for Fractional Diffusion Equations in an Unknown Medium
Bangti Jin, Yavar Kian
In this work, we investigate the recovery of a parameter in a diffusion process given by the order of derivation in time for a class of diffusion type equations, including both cla…