4 citations · 4 across the 2 of their papers we have counts for
6 papers
BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators
Wenjing Wang, Mohan Krishnamoorthy, Juliane Muller +5
The parameters in Monte Carlo (MC) event generators are tuned on experimental measurements by evaluating the goodness of fit between the data and the MC predictions. The relative i…
Classical Optimizers for Noisy Intermediate-Scale Quantum Devices
Wim Lavrijsen, Ana Tudor, Juliane Müller +2
We present a collection of optimizers tuned for usage on Noisy Intermediate-Scale Quantum (NISQ) devices. Optimizers have a range of applications in quantum computing, including th…
Multivariate Rational Approximation
Anthony P. Austin, Mohan Krishnamoorthy, Sven Leyffer +3
We present two approaches for computing rational approximations to multivariate functions, motivated by their effectiveness as surrogate models for high-energy physics (HEP) applic…
Cosmic Inference: Constraining Parameters With Observations and Highly Limited Number of Simulations
Timur Takhtaganov, Zarija Lukic, Juliane Mueller +1
Cosmological probes pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters which characteri…
Adaptive Gaussian process surrogates for Bayesian inference
Timur Takhtaganov, Juliane Müller
We present an adaptive approach to the construction of Gaussian process surrogates for Bayesian inference with expensive-to-evaluate forward models. Our method relies on the fully…
An Efficient Algorithm for Automatic Structure Optimization in X-ray Standing-Wave Experiments
Osman Karslıoğlu, Mathias Gehlmann, Juliane Müller +5
X-ray standing-wave photoemission experiments involving multilayered samples are emerging as unique probes of the buried interfaces that are ubiquitous in current device and materi…