16 citations · 32 across the 7 of their papers we have counts for
3 papers · 1 filter
Machine Learning Closure Audits for LSST Photometric Supernova Cosmology
Ayan Mitra
Modern and next generation supernova cosmology analyses rely on end to end simulations to train photometric classifiers, characterise selection effects, validate light curve models…
Probing Physics Beyond the Standard Model through Combined Analyses of Next-Generation Type Ia Supernova, CMB, and BAO Surveys
Srinivasan Raghunathan, Ayan Mitra, Nikolina Šarčević +11
Observations of Type Ia supernovae (\sne), which probe the late Universe, together with baryon acoustic oscillations (BAO) and the cosmic microwave background (CMB), which probe th…
FlowSN: Neural Simulation-Based Inference under Realistic Selection Effects applied to Supernova Cosmology
Benjamin M. Boyd, Kaisey S. Mandel, Matthew Grayling +10
We present FlowSN, a statistical framework using simulation-based inference (SBI) with normalising flows to account for selection effects in observational astronomy. Failure to acc…