Paper recorded by Signals 4 on 2026-10-08 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-08 on arXiv · recorded by Signals 4 on 2026-10-09
Category: cs.AI · 人工智能 · first seen 2026-10-09
Bifurcations are ubiquitous in physical systems, from structural buckling to fluid and climate dynamics, yet they remain largely unexplored in deep learning. At a symmetry-breaking bifurcation, a single input admits multiple equally valid solutions, violating the one-to-one assumption underlying most learned physical surrogates. We introduce Bi-FORK, a generative framework for learning these one-t