2 papers
physics.acc-ph2026
Data-Driven Optimisation of Superconducting Magnets at CEA Paris-Saclay
Damien F. G. Minenna, Guillaume Dilasser, Robin Penavaire +26
Superconducting magnets for particle accelerators are particularly challenging to design because they involve a large number of coupled physical phenomena and the management of com…
cs.LG2026
XFACTORS: Disentangled Information Bottleneck via Contrastive Supervision
Alexandre Myara, Nicolas Bourriez, Thomas Boyer +3
Disentangled representation learning aims to map independent factors of variation to independent representation components. On one hand, purely unsupervised approaches have proven…