Dingo-Pop uses a transformer to perform amortized, end-to-end population inference from GW strain data in seconds, bypassing per-event Monte Carlo sampling.
Title resolution pending
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
fields
gr-qc 4years
2026 4representative citing papers
Maximum-likelihood-based posterior predictive checks detect model misspecification better than event-level versions for uncertain spin tilts, but current detector sensitivity limits their power; the Gaussian Component Spins model underpredicts high spin magnitudes and overpredicts anti-aligned tilts
B-spline agnostic reconstruction of binary black hole masses from GWTC-4.0 reveals multiple features and a logarithmic hierarchy that impacts Hubble constant measurements, with a low-mass subpopulation isolation method to mitigate systematics.
citing papers explorer
-
End-to-End Population Inference from Gravitational-Wave Strain using Transformers
Dingo-Pop uses a transformer to perform amortized, end-to-end population inference from GW strain data in seconds, bypassing per-event Monte Carlo sampling.
-
Posterior Predictive Checks for Gravitational-wave Populations: Limitations and Improvements
Maximum-likelihood-based posterior predictive checks detect model misspecification better than event-level versions for uncertain spin tilts, but current detector sensitivity limits their power; the Gaussian Component Spins model underpredicts high spin magnitudes and overpredicts anti-aligned tilts
-
Emergent structure in the binary black hole mass distribution and implications for population-based cosmology
B-spline agnostic reconstruction of binary black hole masses from GWTC-4.0 reveals multiple features and a logarithmic hierarchy that impacts Hubble constant measurements, with a low-mass subpopulation isolation method to mitigate systematics.
- Signatures of a subpopulation of hierarchical mergers in the GWTC-4 gravitational-wave dataset