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cs.LG2026
Do Temporal Link Predictors Need Learned Memory? A Smoothed-Count Baseline with a Handful of Parameters
Lisi Qarkaxhija, Ingo Scholtes
Many temporal link predictors summarize past interactions through learned node representations. We examine whether simple counts of recurring interaction patterns can provide compe…
astro-ph.HE2026
Learning Neural Operator Surrogates for the Black Hole Accretion Code
Matthias Nägele, Cedric Bös, Chester Tan +3
General-relativistic magnetohydrodynamic (GR-MHD) simulations are essential for studying black hole accretion, relativistic jets, and magnetic reconnection, yet their computational…