JetSCI is a hybrid JAX-PETSc framework that delivers scalable differentiable finite element simulations and outperforms pure JAX implementations on heterogeneous micromechanics problems.
Deep learning in computational mechanics: a review
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Holomorphic neural networks enforce exact satisfaction of harmonic PDEs for 3D Laplace and elasticity problems using Whittaker representations and boundary-only training.
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JetSCI: A Hybrid JAX-PETSc Framework for Scalable Differentiable Simulation
JetSCI is a hybrid JAX-PETSc framework that delivers scalable differentiable finite element simulations and outperforms pure JAX implementations on heterogeneous micromechanics problems.
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A holomorphic neural network framework for 3D boundary value problems governed by harmonic potentials
Holomorphic neural networks enforce exact satisfaction of harmonic PDEs for 3D Laplace and elasticity problems using Whittaker representations and boundary-only training.