466 citations · 7.4k across the 130 of their papers we have counts for
9 papers · 1 filter
PolySwyft: sequential simulation-based nested sampling
Kilian H. Scheutwinkel, Will Handley, Christoph Weniger +1
We present PolySwyft, a novel, non-amortised simulation-based inference framework that unites the strengths of nested sampling (NS) and neural ratio estimation (NRE) to tackle chal…
Dynamic SBI: Round-free Sequential Simulation-Based Inference with Adaptive Datasets
Huifang Lyu, James Alvey, Noemi Anau Montel +2
Simulation-based inference (SBI) is emerging as a new statistical paradigm for addressing complex scientific inference problems. By leveraging the representational power of deep ne…
How to embed any likelihood into SBI: Application to Planck + Stage IV galaxy surveys and Dynamical Dark Energy
Guillermo Franco Abellán, Noemi Anau Montel, Oleg Savchenko +1
Simulation-based inference (SBI) allows fast Bayesian inference for simulators encoding implicit likelihoods. However, some explicit likelihoods cannot be easily reformulated as si…
A robust neural determination of the source-count distribution of the Fermi-LAT sky at high latitudes
Christopher Eckner, Noemi Anau Montel, Florian List +2
Over the past 16 years, the Fermi Large Area Telescope (LAT) has significantly advanced our view of the GeV gamma-ray sky, yet several key questions remain - such as the compositio…
Sequential simulation-based inference for extreme mass ratio inspirals
Philippa S. Cole, James Alvey, Lorenzo Speri +4
Extreme mass-ratio inspirals pose a difficult challenge in terms of both search and parameter estimation for upcoming space-based gravitational-wave detectors such as LISA. Their s…
Strategic White Paper on AI Infrastructure for Particle, Nuclear, and Astroparticle Physics: Insights from JENA and EuCAIF
Sascha Caron, Andreas Ipp, Gert Aarts +16
Artificial intelligence (AI) is transforming scientific research, with deep learning methods playing a central role in data analysis, simulations, and signal detection across parti…