research
∙
09/21/2023
Enhancing SAEAs with Unevaluated Solutions: A Case Study of Relation Model for Expensive Optimization
Surrogate-assisted evolutionary algorithms (SAEAs) hold significant impo...
share
research
∙
08/26/2023
SyMOT-Flow: Learning optimal transport flow for two arbitrary distributions with maximum mean discrepancy
Finding a transformation between two unknown probability distributions f...
research
∙
04/17/2023
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems
Bayesian methods for solving inverse problems are a powerful alternative...
research
∙
04/10/2023
Approximate Primal-Dual Fixed-Point based Langevin Algorithms for Non-smooth Convex Potentials
The Langevin algorithms are frequently used to sample the posterior dist...
research
∙
03/30/2023
On the convergence of continuous and discrete unbalanced optimal transport models
We consider a Beckmann formulation of an unbalanced optimal transport (U...
research
∙
05/01/2022
Dataset-free Deep learning Method for Low-Dose CT Image Reconstruction
Low-dose CT (LDCT) imaging attracted a considerable interest for the red...
research
∙
08/07/2021
Variable metric extrapolation proximal iterative hard thresholding method for â„“_0 minimization problem
In this paper, we consider the â„“_0 minimization problem whose objective ...
research
∙
02/10/2020
Semi-Implicit Back Propagation
Neural network has attracted great attention for a long time and many re...
research
∙
07/01/2019
A greedy algorithm for sparse precision matrix approximation
Precision matrix estimation is an important problem in statistical data ...
research
∙
03/05/2019
Bayesian inference and uncertainty quantification for image reconstruction with Poisson data
We provide a complete framework for performing infinite-dimensional Baye...
research
∙
01/25/2017
