49 citations · 56 across the 6 of their papers we have counts for
4 papers · 1 filter
Training a neural network to rapidly identify candidate gravitational-wave events in the lower mass gap
Nayyer Raza, Man Leong Chan, Daryl Haggard +5
The physics governing the boundary between the most massive neutron stars (NSs) and the least massive black holes (BHs) is currently uncertain, but could potentially be constrained…
GWSkyNet-Multi II: an updated machine learning model for rapid classification of gravitational-wave events
Nayyer Raza, Man Leong Chan, Daryl Haggard +5
Multi-messenger observations of gravitational waves and electromagnetic emission from compact object mergers offer unique insights into the structure of neutron stars, the formatio…
GWSkyNet II : a refined machine learning pipeline for real-time classification of public gravitational wave alerts
Man Leong Chan, Jess McIver, Ashish Mahabal +12
Electromagnetic follow-up observations of gravitational wave events offer critical insights and provide significant scientific gain from this new class of astrophysical transients.…
Explaining the GWSkyNet-Multi machine learning classifier predictions for gravitational-wave events
Nayyer Raza, Man Leong Chan, Daryl Haggard +5
GWSkyNet-Multi is a machine learning model developed for classification of candidate gravitational-wave events detected by the LIGO and Virgo observatories. The model uses limited…