3 papers
stat.ML2026
Variance-Reduced Diffusion Sampling via Target Score Identity
Alois Duston, Tan Bui-Thanh
We study variance reduction for score estimation and diffusion-based sampling in settings where the clean (target) score is available or can be approximated. Starting from the Targ…
math.NA2025
Improvements on uncertainty quantification with variational autoencoders
Andrea Tonini, Tan Bui-Thanh, Francesco Regazzoni +2
Inverse problems aim to determine model parameters of a mathematical problem from given observational data. Neural networks can provide an efficient tool to solve these problems. I…
math.NA2023
An autoencoder compression approach for accelerating large-scale inverse problems
Jonathan Wittmer, Jacob Badger, Hari Sundar +1
PDE-constrained inverse problems are some of the most challenging and computationally demanding problems in computational science today. Fine meshes that are required to accurately…