Automatic differentiation of FEniCS and Firedrake models in Julia
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Updated
Mar 21, 2021 - Julia
Automatic differentiation of FEniCS and Firedrake models in Julia
Workshop materials for training in scientific computing and scientific machine learning
A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
Julia interface to MITgcm
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