A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
A hybrid model combines diffusion and neural operator methods for stress prediction in hyperelastic materials.
Hyperelastic bodies in Riemannian manifolds can levitate due to curvature-induced forces.
This work ensures stability in POD basis interpolation for pMOR in hyperelasticity.
Study on materials with disclinations, limiting their size.
Bayesian-guided method selects optimal design from large candidate pool.
In this work, we develop Gaussian process regression (GPR) models of hyperelastic material behavior. First, we consider the direct approach of modeling the components of the Cauchy stress tensor as a function of the components of the Finger stretch tensor in a Gaussian process. We then consider an improvement on this a…
Local laGPR speeds up multiscale mechanics simulations without neural networks.
Continuum mechanics theory describes skin's complex anisotropic behavior.
Neural operators correct PDE residuals to improve BIP solutions.
Geometrically reformulates Cosserat solid mechanics using differential geometry.