2 citations · 2 across the 3 of their papers we have counts for
4 papers
Fast Uncertainty Quantification of Spent Nuclear Fuel with Neural Networks
Arnau Albà, Andreas Adelmann, Lucas Münster +2
The accurate calculation and uncertainty quantification of the characteristics of spent nuclear fuel (SNF) play a crucial role in ensuring the safety, efficiency, and sustainabilit…
Lasso Monte Carlo, a Variation on Multi Fidelity Methods for High Dimensional Uncertainty Quantification
Arnau Albà, Romana Boiger, Dimitri Rochman +1
Uncertainty quantification (UQ) is an active area of research, and an essential technique used in all fields of science and engineering. The most common methods for UQ are Monte Ca…
Retrieval of aerosol properties from in situ, multi-angle light scattering measurements using invertible neural networks
Romana Boiger, Rob L. Modini, Alireza Moallemi +3
Atmospheric aerosols have a major influence on the earths climate and public health. Hence, studying their properties and recovering them from light scattering measurements is of g…
Fast, efficient and flexible particle accelerator optimisation using densely connected and invertible neural networks
Renato Bellotti, Romana Boiger, Andreas Adelmann
Particle accelerators are enabling tools for scientific exploration and discovery in various disciplines. Finding optimized operation points for these complex machines is a challen…