38 citations
- University of StuttgartDE17 papers
- Simulation Technologies (United States)US2 papers
- American Institute of Aeronautics and AstronauticsUS1 paper
- AO FoundationCH1 paper
- Chalmers University of TechnologySE1 paper
- École Polytechnique Fédérale de LausanneCH1 paper
- Flatiron Health (United States)US1 paper
- Flatiron Institute1 paper
- Heidelberg UniversityDE1 paper
- Karlsruhe Institute of TechnologyDE1 paper
- Laboratoire de Probabilités, Statistique et ModélisationFR1 paper
- Lincoln Agritech (New Zealand)NZ1 paper
17 papers
Elucidating contact electrification mechanism of water
Vasily Artemov, Laura Frank, Roman Doronin +6
The open water surface is known to be charged. Yet, the magnitude of the charge and the physical mechanism of the charging remain unclear, causing heated debates across the scienti…
Non-stationary max-stable models with an application to heavy rainfall data
Carolin Forster, Marco Oesting
In recent years, parametric models for max-stable processes have become a popular choice for modeling spatial extremes because they arise as the asymptotic limit of rescaled maxima…
Certified machine learning: Rigorous a posteriori error bounds for PDE defined PINNs
Birgit Hillebrecht, Benjamin Unger
Prediction error quantification in machine learning has been left out of most methodological investigations of neural networks, for both purely data-driven and physics-informed app…
A continuum mechanical porous media model for vertebroplasty: Numerical simulations and experimental validation
Zubin Trivedi, Dominic Gehweiler, Jacek K. Wychowaniec +4
The outcome of vertebroplasty is hard to predict due to its dependence on complex factors like bone cement and marrow rheologies. Cement leakage could occur if the procedure is don…
Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy
Paul-Christian Bürkner, Maximilian Scholz, Stefan T. Radev
Probabilistic (Bayesian) modeling has experienced a surge of applications in almost all quantitative sciences and industrial areas. This development is driven by a combination of s…
Intuitive Joint Priors for Bayesian Linear Multilevel Models: The R2D2M2 prior
Javier Enrique Aguilar, Paul-Christian Bürkner
The training of high-dimensional regression models on comparably sparse data is an important yet complicated topic, especially when there are many more model parameters than observ…