5 papers
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…
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…
Wallpaper Group-Based Mechanical Metamaterials: Dataset Including Mechanical Responses
Fleur Hendriks, Vlado Menkovski, Martin DoškáŠ+3
Mechanical metamaterials often exhibit pattern transformations through instabilities, enabling applications in, e.g., soft robotics, sound reduction, and biomedicine. These transfo…
Similarity Equivariant Graph Neural Networks for Homogenization of Metamaterials
Fleur Hendriks, Vlado Menkovski, Martin DoškáŠ+2
Soft, porous mechanical metamaterials exhibit pattern transformations that may have important applications in soft robotics, sound reduction and biomedicine. To design these innova…
Understanding complex crowd dynamics with generative neural simulators
Koen Minartz, Fleur Hendriks, Simon Martinus Koop +2
Understanding the dynamics of pedestrian crowds is an outstanding challenge crucial for designing efficient urban infrastructure and ensuring safe crowd management. To this end, bo…