3 papers
cs.CE2025
COMMET: orders-of-magnitude speed-up in finite element method via batch-vectorized neural constitutive updates
Benjamin Alheit, Mathias Peirlinck, Siddhant Kumar
Constitutive evaluations often dominate the computational cost of finite element (FE) simulations whenever material models are complex. Neural constitutive models (NCMs) offer a hi…
eess.IV2025
Full-field surrogate modeling of cardiac function encoding geometric variability
Elena Martinez, Beatrice Moscoloni, Matteo Salvador +3
Combining physics-based modeling with data-driven methods is critical to enabling the translation of computational methods to clinical use in cardiology. The use of rigorous differ…
cs.LG2025
Can KAN CANs? Input-convex Kolmogorov-Arnold Networks (KANs) as hyperelastic constitutive artificial neural networks (CANs)
Prakash Thakolkaran, Yaqi Guo, Shivam Saini +3
Traditional constitutive models rely on hand-crafted parametric forms with limited expressivity and generalizability, while neural network-based models can capture complex material…