A Differentiable Framework for Inverse Identification of Heterogeneous Cohesive Laws
physics.comp-ph, cs.CE
Submitted: 2026-10-24
Updated: 2026-10-24
Related papers
- Refining Machine Learning Potentials through Thermodynamic Theory of Phase Transitions
- Polyconvex neural-network surrogates with learned paired directional features for anisotropic hyperelastic homogenization
- Learning Spectrally Optimised Mesh-Free Discretisations
- Feature-preserving Latent-EnKF for Data Assimilation of Flows with Shocks
- chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations
- Omnisolver: An extensible interface to Ising spin-glass and QUBO solvers: adding a distributed GPU brute-force plugin