additional corrections supervised chapter
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@@ -63,7 +63,7 @@ for all parameters of $\mathcal P(\mathbf{x}, \nu)$, e.g.,
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we omit $\nu$ in the following, assuming that this is a
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given model parameter with which the NN should not interact.
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Naturally, it can vary within the solution manifold that we're interested in,
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but $\nu$ will not be the output of a NN representation. If this is the case, we can omit
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but $\nu$ will not be the output of an NN representation. If this is the case, we can omit
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providing $\partial \mathcal P_i / \partial \nu$ in our solver. However, the following learning process
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naturally transfers to including $\nu$ as a degree of freedom.
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