8 citations · 16 across the 7 of their papers we have counts for
7 papers
Neural Posterior Estimation of Terrain Parameters from Radar Sounder Data
Jordy Dal Corso, Annalena Kofler, Marco Cortellazzi +2
Radar sounders are electromagnetic instruments that can probe deep into the subsurface of Earth and other planetary bodies by processing the echo of transmitted radar waves. Conven…
Gradient estimators for parameter inference in discrete stochastic kinetic models
Ludwig Burger, Annalena Kofler, Lukas Heinrich +1
Stochastic kinetic models are ubiquitous in physics, yet inferring their parameters from experimental data remains challenging. For deterministic models, parameter inference often…
Eccentricity constraints disfavor single-single capture in nuclear star clusters as the origin of all LIGO-Virgo-KAGRA binary black holes
Nihar Gupte, M. Coleman Miller, Rhiannon Udall +12
Multiple formation pathways have been proposed for the origin of binary black holes (BBHs). These include isolated binary evolution and dynamical assembly in dense stellar environm…
Flexible Gravitational-Wave Parameter Estimation with Transformers
Annalena Kofler, Maximilian Dax, Stephen R. Green +6
Gravitational-wave data analysis relies on accurate and efficient methods to extract physical information from noisy detector signals, yet the increasing rate and complexity of obs…
Fast and accurate parameter estimation of high-redshift sources with the Einstein Telescope
Filippo Santoliquido, Jacopo Tissino, Ulyana Dupletsa +9
The Einstein Telescope (ET), along with other third-generation gravitational wave (GW) detectors, will be a key instrument for detecting GWs in the coming decades. However, analyzi…
Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle Physics
Annalena Kofler, Vincent Stimper, Mikhail Mikhasenko +2
High-energy physics requires the generation of large numbers of simulated data samples from complex but analytically tractable distributions called matrix elements. Surrogate model…
Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels
Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax +4
Inferring atmospheric properties of exoplanets from observed spectra is key to understanding their formation, evolution, and habitability. Since traditional Bayesian approaches to…