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cs.LG2026
Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model
Max Weinmann, Miriam Klopotek
We study how unsupervised autoencoders trained on microscopic spin configurations from the Ising model learn macroscopic, theory-relevant variables underlying the data-generating p…
cs.LG2025
Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations
Patrick Egenlauf, Iva Březinová, Sabine Andergassen +1
Out-of-equilibrium quantum many-body systems exhibit rapid correlation buildup that underlies many emerging phenomena. Exact wave-function methods to describe this scale exponentia…