3 papers
astro-ph.IM2026
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…
cs.LG2025
A Guide to Robust Generalization: The Impact of Architecture, Pre-training, and Optimization Strategy
Maxime Heuillet, Rishika Bhagwatkar, Jonas Ngnawé +6
Deep learning models operating in the image domain are vulnerable to small input perturbations. For years, robustness to such perturbations was pursued by training models from scra…
astro-ph.IM2025
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…