69 citations · 123 across the 4 of their papers we have counts for
4 papers
Optimal statistical inference in the presence of systematic uncertainties using neural network optimization based on binned Poisson likelihoods with nuisance parameters
Stefan Wunsch, Simon Jörger, Roger Wolf +1
Data analysis in science, e.g., high-energy particle physics, is often subject to an intractable likelihood if the observables and observations span a high-dimensional input space.…
Reducing the dependence of the neural network function to systematic uncertainties in the input space
Stefan Wunsch, Simon Jörger, Roger Wolf +1
Applications of neural networks to data analyses in natural sciences are complicated by the fact that many inputs are subject to systematic uncertainties. To control the dependence…
Identifying the relevant dependencies of the neural network response on characteristics of the input space
Stefan Wunsch, Raphael Friese, Roger Wolf +1
The relation between the input and output spaces of neural networks (NNs) is investigated to identify those characteristics of the input space that have a large influence on the ou…
Magnetic hysteresis effects in superconducting coplanar microwave resonators
Daniel Bothner, Tobias Gaber, Matthias Kemmler +4
We performed transmission spectroscopy experiments on coplanar half wavelength niobium resonators at a temperature T=4.2 K. We observe not only a strong dependence of the quality f…