2 papers
stat.ML2026
Uncertainty-Aware Surrogate-based Amortized Bayesian Inference for Computationally Expensive Models
Stefania Scheurer, Philipp Reiser, Tim Brünnette +3
Bayesian inference typically relies on a large number of model evaluations to estimate posterior distributions. Established methods like Markov Chain Monte Carlo (MCMC) and Amortiz…
physics.geo-ph2025
HydroStartML: A combined machine learning and physics-based approach to reduce hydrological model spin-up time
Louisa Pawusch, Stefania Scheurer, Wolfgang Nowak +1
Finding the initial depth-to-water table (DTWT) configuration of a catchment is a critical challenge when simulating the hydrological cycle with integrated models, significantly im…