Pages that link to "Item:Q2024599"
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The following pages link to A kernel method for learning constitutive relation in data-driven computational elasticity (Q2024599):
Displaying 14 items.
- Data-driven non-linear elasticity: constitutive manifold construction and problem discretization (Q683898) (← links)
- Hyperelastic membrane modelling based on data-driven constitutive relations (Q776954) (← links)
- A manifold learning approach to data-driven computational elasticity and inelasticity (Q1639583) (← links)
- Phase distribution and properties identification of heterogeneous materials: a data-driven approach (Q2072688) (← links)
- Accelerating the distance-minimizing method for data-driven elasticity with adaptive hyperparameters (Q2171513) (← links)
- Unsupervised discovery of interpretable hyperelastic constitutive laws (Q2237006) (← links)
- Data-based derivation of material response (Q2310702) (← links)
- Derivation of heterogeneous material laws via data-driven principal component expansions (Q2319393) (← links)
- Thermodynamically consistent machine-learned internal state variable approach for data-driven modeling of path-dependent materials (Q2679297) (← links)
- Distance-preserving manifold denoising for data-driven mechanics (Q2683440) (← links)
- JAX-FEM: a differentiable GPU-accelerated 3D finite element solver for automatic inverse design and mechanistic data science (Q6112664) (← links)
- Computation‐with‐confidence for static elasticity: Data‐driven approach with order statistics (Q6121553) (← links)
- Data-driven solvers for strongly nonlinear material response (Q6553311) (← links)
- Data-driven confidence bound for structural response using segmented least squares: a mixed-integer programming approach (Q6614962) (← links)
