A material's energy law can be recovered uniquely from boundary energy measurements whenever the loading set separates candidate laws, and maxout neural networks provide provably convergent approximations.
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A well-posed variational approach to the identification and convergent approximation of material laws from boundary data
A material's energy law can be recovered uniquely from boundary energy measurements whenever the loading set separates candidate laws, and maxout neural networks provide provably convergent approximations.