Pages that link to "Item:Q2246355"

The following pages link to Learning viscoelasticity models from indirect data using deep neural networks (Q2246355):

Displaying 21 items.

• Learning constitutive relations from indirect observations using deep neural networks (Q781968) (← links)
• Sobolev training of thermodynamic-informed neural networks for interpretable elasto-plasticity models with level set hardening (Q2021962) (← links)
• Non-invasive inference of thrombus material properties with physics-informed neural networks (Q2022055) (← links)
• Frame-independent vector-cloud neural network for nonlocal constitutive modeling on arbitrary grids (Q2060111) (← links)
• Simulation of Maxwell equation based on an ADI approach and integrated radial basis function-generalized moving least squares (IRBF-GMLS) method with reduced order algorithm based on proper orthogonal decomposition (Q2085936) (← links)
• Physics-based self-learning recurrent neural network enhanced time integration scheme for computing viscoplastic structural finite element response (Q2096901) (← links)
• RI-IGABEM for 3D viscoelastic problems with body force (Q2136744) (← links)
• Data-driven tissue mechanics with polyconvex neural ordinary differential equations (Q2160446) (← links)
• Learning deep implicit Fourier neural operators (IFNOs) with applications to heterogeneous material modeling (Q2160481) (← links)
• Hidden physics model for parameter estimation of elastic wave equations (Q2236961) (← links)
• Learning nonlocal constitutive models with neural networks (Q2237430) (← links)
• Recurrent neural networks (RNNs) learn the constitutive law of viscoelasticity (Q2241874) (← links)
• A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation (Q2319404) (← links)
• A deep learning energy method for hyperelasticity and viscoelasticity (Q2671703) (← links)
• Model-free data-driven viscoelasticity in the frequency domain (Q2679436) (← links)
• Implicit constitutive modelling for viscoplasticity using neural networks (Q4253789) (← links)
• Data-driven anisotropic finite viscoelasticity using neural ordinary differential equations (Q6097591) (← links)
• JAX-FEM: a differentiable GPU-accelerated 3D finite element solver for automatic inverse design and mechanistic data science (Q6112664) (← links)
• The anisotropic graph neural network model with multiscale and nonlinear characteristic for turbulence simulation (Q6185144) (← links)
• An indirect training approach for implicit constitutive modelling using recurrent neural networks and the virtual fields method (Q6497200) (← links)
• A multi-resolution physics-informed recurrent neural network: formulation and application to musculoskeletal systems (Q6558963) (← links)