3 papers
math.OC2026
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…
q-bio.QM2025
Quantitative assessment of biological dynamics with aggregate data
Stephen McCoy, Daniel McBride, D. Katie McCullough +4
We develop and apply a learning framework for parameter estimation in initial value problems that are assessed only indirectly via aggregate data such as sample means and/or standa…
math.NA2024
Hamiltonian Monte Carlo methods for spectroscopy data analysis
Daniel McBride, Ioannis Sgouralis
We present a scalable Bayesian framework for the analysis of confocal fluorescence spectroscopy data, addressing key limitations in traditional fluorescence correlation spectroscop…