JetSCI is a hybrid JAX-PETSc framework that delivers scalable differentiable finite element simulations and outperforms pure JAX implementations on heterogeneous micromechanics problems.
Differentiable program- ming across the pde and machine learning barrier
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A neural network learns parameter-dependent viscosity models for ice that satisfy physical invariants and generalize from velocity or stress data.
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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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Learning parameter-dependent shear viscosity from data, with application to sea and land ice
A neural network learns parameter-dependent viscosity models for ice that satisfy physical invariants and generalize from velocity or stress data.