Pages that link to "Item:Q1639585"
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The following pages link to kPCA-based parametric solutions within the PGD framework (Q1639585):
Displaying 10 items.
- Data-driven non-linear elasticity: constitutive manifold construction and problem discretization (Q683898) (← links)
- A manifold learning approach to data-driven computational elasticity and inelasticity (Q1639583) (← links)
- Big data in experimental mechanics and model order reduction: today's challenges and tomorrow's opportunities (Q1639599) (← links)
- Model-free data-driven computational mechanics enhanced by tensor voting (Q2020810) (← links)
- Reduced-order modeling via proper generalized decomposition for uncertainty quantification of frequency response functions (Q2096868) (← links)
- A deep learning-based hybrid approach for the solution of multiphysics problems in electrosurgery (Q2179220) (← links)
- Some applications of compressed sensing in computational mechanics: model order reduction, manifold learning, data-driven applications and nonlinear dimensionality reduction (Q2281470) (← links)
- Parametric stress field solutions for heterogeneous materials using proper generalized decomposition (Q2683330) (← links)
- PGD for solving multidimensional and parametric models (Q5253312) (← links)
- A nonintrusive proper generalized decomposition scheme with application in biomechanics (Q6557594) (← links)
