arxivcs.LGcond-mat.dis-nncond-mat.stat-mech2026-07-11
Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model
We study how unsupervised autoencoders trained on microscopic spin configurations from the Ising model learn macroscopic, theory-relevant variables underlying the data-generating process. Without embedding domain knowledge, we mimic a typical discovery setting: We quantify learni…