3 papers
astro-ph.IM2026
GW-FALCON: A Novel Feature-Driven Deep Learning Approach for Early Warning Alerts of BNS and NSBH Inspirals in Next-Generation GW Observatories
Grigorios Papigkiotis, Georgios Vardakas, Nikolaos Stergioulas
Next-generation GW observatories such as the ET and CE will detect BNS and NSBH inspirals with high SNRs and long in-band durations, making systematic early-warning alerts both fea…
astro-ph.HE2025
Assessing Universal Relations for Rapidly Rotating Neutron Stars: Insights from an Interpretable Deep Learning Perspective
Grigorios Papigkiotis, Georgios Vardakas, Nikolaos Stergioulas
Relations between stellar properties independent of the nuclear equation of state offer profound insights into neutron star physics and have practical applications in data analysis…
cs.LG2025
Counterfactual Explanations for k-means and Gaussian Clustering
Georgios Vardakas, Antonia Karra, Evaggelia Pitoura +1
Counterfactuals have been recognized as an effective approach to explain classifier decisions. Nevertheless, they have not yet been considered in the context of clustering. In this…