research
∙
08/28/2023
Reinforcement Learning for Sampling on Temporal Medical Imaging Sequences
Accelerated magnetic resonance imaging resorts to either Fourier-domain ...
share
research
∙
03/22/2022
Multi-layer Clustering-based Residual Sparsifying Transform for Low-dose CT Image Reconstruction
The recently proposed sparsifying transform models incur low computation...
research
∙
11/17/2021
Single-pass Object-adaptive Data Undersampling and Reconstruction for MRI
There is much recent interest in techniques to accelerate the data acqui...
research
∙
10/28/2021
Physics-Driven Learning of Wasserstein GAN for Density Reconstruction in Dynamic Tomography
Object density reconstruction from projections containing scattered radi...
research
∙
03/26/2021
Model-based Reconstruction with Learning: From Unsupervised to Supervised and Beyond
Many techniques have been proposed for image reconstruction in medical i...
research
∙
02/12/2021
Stochastic Gradient Langevin Dynamics with Variance Reduction
Stochastic gradient Langevin dynamics (SGLD) has gained the attention of...
research
∙
07/21/2020
Spectral estimation from simulations via sketching
Sketching is a stochastic dimension reduction method that preserves geom...
research
∙
01/17/2020
Predictability limit of partially observed systems
Applications from finance to epidemiology and cyber-security require acc...
research
∙
01/24/2019