258 citations · 1k across the 30 of their papers we have counts for
31 papers
Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations
Jonas Beck, Nathanael Bosch, Michael Deistler +4
Ordinary differential equations (ODEs) are widely used to describe dynamical systems in science, but identifying parameters that explain experimental measurements is challenging. I…
Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation
Julius Vetter, Guy Moss, Cornelius Schröder +2
Scientific modeling applications often require estimating a distribution of parameters consistent with a dataset of observations - an inference task also known as source distributi…
Amortized Bayesian Decision Making for simulation-based models
Mila Gorecki, Jakob H. Macke, Michael Deistler
Simulation-based inference (SBI) provides a powerful framework for inferring posterior distributions of stochastic simulators in a wide range of domains. In many settings, however,…
Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal Layers
Guy Moss, Vjeran Višnjević, Olaf Eisen +4
The ice shelves buttressing the Antarctic ice sheet determine the rate of ice-discharge into the surrounding oceans. The geometry of ice shelves, and hence their buttressing streng…
Adversarial robustness of amortized Bayesian inference
Manuel Glöckler, Michael Deistler, Jakob H. Macke
Bayesian inference usually requires running potentially costly inference procedures separately for every new observation. In contrast, the idea of amortized Bayesian inference is t…
Flow Matching for Scalable Simulation-Based Inference
Maximilian Dax, Jonas Wildberger, Simon Buchholz +3
Neural posterior estimation methods based on discrete normalizing flows have become established tools for simulation-based inference (SBI), but scaling them to high-dimensional pro…