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cs.LG2026
Equivariant Flow Matching for Symmetry-Breaking Bifurcation Problems
Fleur Hendriks, OndÅej RokoÅ¡, Martin DoÅ¡káŠ+2
Bifurcation phenomena in nonlinear dynamical systems often lead to multiple coexisting stable solutions, particularly in the presence of symmetry breaking. Deterministic machine le…
cs.LG2026
Auto-Regressive U-Net for Full-Field Prediction of Shrinkage-Induced Damage in Concrete
Liya Gaynutdinova, Petr Havlásek, OndÅej RokoÅ¡ +2
This paper introduces a deep learning approach for predicting time-dependent full-field damage in concrete. The study uses an auto-regressive U-Net model to predict the evolution o…
cs.LG2026★ 1 cited
Homogenization with Guaranteed Bounds via Primal-Dual Physically Informed Neural Networks
Liya Gaynutdinova, Martin DoÅ¡káÅ, OndÅej RokoÅ¡ +1
Physics-informed neural networks (PINNs) have shown promise in solving partial differential equations (PDEs) relevant to multiscale modeling, but they often fail when applied to ma…