3 papers
math.NA2026
Preserving Structure in Variational Data Assimilation of Hyperbolic Conservation Laws via Regularization
Yao Xiao, Anne Gelb
Hyperbolic conservation laws pose a challenging setting for variational data assimilation, since the Gaussian assumption imposes a smoothness that smears jump discontinuities. A sp…
math.NA2025
Joint Signal Recovery and Uncertainty Quantification via the Residual Prior Transform
Yao Xiao, Anne Gelb
Conventional priors used for signal recovery are often limited by the assumption that the type of a signal's variability, such as piecewise constant or linear behavior, is known an…
math.NA2025
A new sparsity promoting residual transform operator for Lasso regression
Yao Xiao, Anne Gelb, Aditya Viswanathan
Lasso regression is a widely employed approach within the regularization framework used to promote sparsity and recover piecewise smooth signals $f:[a,b) \rightarrow \math…