4 papers
Distribution-Agnostic Isocontour Confidence Bounds for Robust Uncertainty Visualization of Scalar Field Data
Timbwaoga A. J. Ouermi, Nina M. Gottschling, Alex Gorczowski +1
Uncertainty visualization has been shown to be pivotal for conveying the reliability of features extracted from scalar fields. Features represented by isocontours, mean isocontours…
Average Kernel Sizes -- Computable Sharp Accuracy Bounds for Inverse Problems
Nina M. Gottschling, David Iagaru, Jakob Gawlikowski +1
The reconstruction of an unknown quantity from noisy measurements is a mathematical problem relevant in most applied sciences, for example, in medical imaging, radar inverse scatte…
On the existence of optimal multi-valued decoders and their accuracy bounds for ill-posed inverse problems
Nina Maria Gottschling, Paolo Campodonico, Vegard Antun +1
Ill-posed inverse problems occur everywhere in the sciences including medical imaging, radar, astronomy etc., yielding underdetermined or ill-posed linear (non-linear) reconstructi…
On Hallucinations in Inverse Problems: Fundamental Limits and Provable Assessment Methods
David Iagaru, Nina M. Gottschling, Anders C. Hansen +1
Artificial intelligence (AI) has transformed imaging inverse problems, from medical diagnostics to Earth observation. Yet deep neural networks can produce hallucinations, realistic…