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math.ST2026
Posterior contraction under misspecification and heteroscedasticity in non-linear inverse problems
Fanny Seizilles, Maximilian Siebel
In many practical and numerical inverse problems, the exact data log-likelihood is not fully accessible, motivating the use of surrogate models. We study heteroscedastic nonparamet…
math.ST2025
Convergence Rates for the Maximum A Posteriori Estimator in PDE-Regression Models with Random Design
Maximilian Siebel
We consider the statistical inverse problem of recovering a parameter from data arising from the Gaussian regression problem \begin{equation*} Y = \mathscr{G}(θ)(Z)+\…
math.ST2024
Lower Bounds for Nonparametric Estimation of Ordinary Differential Equations
Christof Schötz, Maximilian Siebel
We noisily observe solutions of an ordinary differential equation at given times, where lives in a -dimensional state space. The model function is unknow…