3 papers
cs.LG2026
Reference-free logged energy-oracle recovery for neural approximations of symmetric coercive variational problems: conforming Riesz reconstruction and archive-level selection
Karim Bounja, Lahcen Laayouni, Boujemaa Achchab +1
Neural PDE training yields a finite checkpoint archive, yet its logged energy errors are inaccessible without the exact solution, while loss-based selection does not necessarily re…
cs.LG2026
A Mosco sufficient condition for intrinsic stability of non-unique convex Empirical Risk Minimization
Karim Bounja, Lahcen Laayouni, Abdeljalil Sakat
Empirical risk minimization (ERM) stability is usually studied via single-valued outputs, while convex non-strict losses yield set-valued minimizers. We identify Painlevé-Kuratowsk…
cs.LG2025
KD-PINN: Knowledge-Distilled PINNs for ultra-low-latency real-time neural PDE solvers
Karim Bounja, Lahcen Laayouni, Abdeljalil Sakat
This work introduces Knowledge-Distilled Physics-Informed Neural Networks (KD-PINN), a framework that transfers the predictive accuracy of a high-capacity teacher model to a compac…