5 citations · 8 across the 6 of their papers we have counts for
7 papers
Mixed neural posterior estimation for simulators with discrete and continuous parameters
Jan Boelts, Cornelius Schröder, Jonas Beck +3
Neural Posterior Estimation (NPE) enables rapid parameter inference for complex simulators with intractable likelihoods. NPE trains an inference network to estimate a probability d…
Scalable Simulation-Based Model Inference with Test-Time Complexity Control
Manuel Gloeckler, J. P. Manzano-Patrón, Stamatios N. Sotiropoulos +2
Simulation plays a central role in scientific discovery. In many applications, the bottleneck is no longer running a simulator; it is choosing among large families of plausible sim…
Head-to-Head autonomous racing at the limits of handling in the A2RL challenge
Simon Hoffmann, Simon Sagmeister, Tobias Betz +17
Autonomous racing presents a complex challenge involving multi-agent interactions between vehicles operating at the limit of performance and dynamics. As such, it provides a valuab…
FNOPE: Simulation-based inference on function spaces with Fourier Neural Operators
Guy Moss, Leah Sophie Muhle, Reinhard Drews +2
Simulation-based inference (SBI) is an established approach for performing Bayesian inference on scientific simulators. SBI so far works best on low-dimensional parametric models.…
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…
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…
Simultaneous identification of models and parameters of scientific simulators
Cornelius Schröder, Jakob H. Macke
Many scientific models are composed of multiple discrete components, and scientists often make heuristic decisions about which components to include. Bayesian inference provides a…