Pages that link to "Item:Q6554056"
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The following pages link to Meshless physics-informed deep learning method for three-dimensional solid mechanics (Q6554056):
Displaying 10 items.
- A nonlocal energy-informed neural network for peridynamic correspondence material models (Q6545792) (← links)
- Dynamically configured physics-informed neural network in topology optimization applications (Q6550166) (← links)
- An implicit updated Lagrangian fragile points method with a support domain refinement scheme for solving large deformation problems (Q6557506) (← links)
- Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains (Q6569914) (← links)
- Neuro-PINN: a hybrid framework for efficient nonlinear projection equation solutions (Q6569923) (← links)
- Variational temporal convolutional networks for I-FENN thermoelasticity (Q6588274) (← links)
- Transfer learning enhanced nonlocal energy-informed neural network for quasi-static fracture in rock-like materials (Q6595896) (← links)
- Interpretable physics-encoded finite element network to handle concentration features and multi-material heterogeneity in hyperelasticity (Q6609781) (← links)
- Physics informed self-supervised segmentation of elastic composite materials (Q6641894) (← links)
- Finite element-integrated neural network framework for elastic and elastoplastic solids (Q6663275) (← links)
