3 papers
stat.ME2026
Confidence intervals for functionals in constrained inverse problems via data-adaptive sampling-based calibration
Michael Stanley, Pau Batlle, Pratik Patil +2
We address functional uncertainty quantification for ill-posed inverse problems where it is possible to evaluate a possibly rank-deficient forward model, the observation noise dist…
math.ST2025
Simultaneous Frequentist Calibration of Confidence Regions for Multiple Functionals in Constrained Inverse Problems
Pau Batlle, Pratik Patil, Michael Stanley +3
Many scientific analyses require simultaneous comparison of multiple functionals of an unknown signal at once, calling for multidimensional confidence regions with guaranteed simul…
cs.LG2025
Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots
Théo Bourdais, Pau Batlle, Xianjin Yang +3
Most problems within and beyond the scientific domain can be framed into one of the following three levels of complexity of function approximation. Type 1: Approximate an unknown f…