1 citations · 1 across the 2 of their papers we have counts for
7 papers
Field-level multi-tracers simulation-based inference of cosmological parameters from 3D maps
Giulio Scelfo, Satvik Mishra, Mauro Rigo +2
Extracting maximum cosmological information from current and upcoming large-scale structure data requires going beyond summary statistics as currently used in likelihood-based infe…
CIGaRS I: Combined simulation-based inference from type Ia supernovae and host photometry
Konstantin Karchev, Roberto Trotta, Raul Jimenez
Using type Ia supernovae as cosmological probes requires empirical corrections that are correlated with their host environment. Here we present a unified Bayesian hierarchical mode…
Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration
LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz +63
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that cha…
Simulation-based population inference of LISA's Galactic binaries: Bypassing the global fit
Rahul Srinivasan, Enrico Barausse, Natalia Korsakova +1
The Laser Interferometer Space Antenna (LISA) is expected to detect thousands of individually resolved gravitational wave sources, overlapping in time and frequency, on top of unre…
STAR NRE: Solving supernova selection effects with set-based truncated auto-regressive neural ratio estimation
Konstantin Karchev, Roberto Trotta
Accounting for selection effects in supernova type Ia (SN Ia) cosmology is crucial for unbiased cosmological parameter inference -- even more so for the next generation of large, m…
Near-instantaneous Atmospheric Retrievals and Model Comparison with FASTER
Anna Lueber, Konstantin Karchev, Chloe Fisher +3
In the era of the James Webb Space Telescope (JWST), the dramatic improvement in the spectra of exoplanetary atmospheres demands a corresponding leap forward in our ability to anal…