Labrador is a domain-optimized neural posterior estimation tool achieving 1% median importance-sampling efficiency and first extensive coverage of long-duration low-mass gravitational wave signals through equivariance and a stable procedure for differing priors.
Title resolution pending
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
verdicts
UNVERDICTED 5representative citing papers
First spectral covariance analysis of SGWB data yields upper bounds on non-stationary correlations that translate into mass-dependent limits on high-redshift PBH merger rates.
VIGILant applies tree-based models and a ResNet CNN to classify Virgo O3b glitches with 98% accuracy and has been deployed for daily use with an interactive dashboard.
The work calculates scalar quasinormal mode spectra for a rotating quantum-corrected black hole and constructs a methodological pipeline to infer the quantum correction parameter from gravitational-wave ringdown data using informative priors.
Residuals after subtracting best-fit waveforms from GWTC-3 events show no significant deviation from noise according to three standard goodness-of-fit tests.
citing papers explorer
-
labrador: A domain-optimized machine-learning tool for gravitational wave inference
Labrador is a domain-optimized neural posterior estimation tool achieving 1% median importance-sampling efficiency and first extensive coverage of long-duration low-mass gravitational wave signals through equivariance and a stable procedure for differing priors.
-
The First Upper Bound on the Non-Stationary Gravitational Wave Background and its Implication on the High Redshift Binary Black Hole Merger Rate
First spectral covariance analysis of SGWB data yields upper bounds on non-stationary correlations that translate into mass-dependent limits on high-redshift PBH merger rates.
-
VIGILant: an automatic classification pipeline for glitches in the Virgo detector
VIGILant applies tree-based models and a ResNet CNN to classify Virgo O3b glitches with 98% accuracy and has been deployed for daily use with an interactive dashboard.
-
The quasinormal modes of the rotating quantum corrected black holes
The work calculates scalar quasinormal mode spectra for a rotating quantum-corrected black hole and constructs a methodological pipeline to infer the quantum correction parameter from gravitational-wave ringdown data using informative priors.
-
Residual Test for the Third Gravitational-Wave Transient Catalog
Residuals after subtracting best-fit waveforms from GWTC-3 events show no significant deviation from noise according to three standard goodness-of-fit tests.