Commit 21336cf7 by Philipp Arras

Fixups

parent 3e40b830
Pipeline #35441 passed with stage
in 21 seconds
 ... ... @@ -54,6 +54,9 @@ \maketitle \VerbatimFootnotes \section*{Why should I read this guide?} Let us define: $d$ is the data vector and $s$ is the physical field, you want to learn from $d$ in a Bayesian fashion. Bayesian reconstruction algorithms may be viewed in terms of three basic building blocks. ... ... @@ -293,7 +296,9 @@ This test does the same as the test for the adjointness above. So far, we have wrapped the derivative of the response in a \texttt{LinearOperator}. The other thing to be done is to make the function \texttt{R(s)} field-aware. Rewrite it such that it takes a field in signal space as input and returns a field in data space. as input and returns a field in data space. Make sure that all methods you have implemented can deal with arbitrary sizes of the signal space. All pixel volumes should be taken care of by you. \section*{Example: $\gamma$-ray imaging} The information a $\gamma$-ray astronomer would provide to the algorithm (in the ... ... @@ -314,5 +319,4 @@ Why is this already sufficient? s_1+s_2) = \alpha R(s_1) + R(s_2)$.} Thus,$R' = R$and$R'^\dagger = R^\dagger$. All in all, we need an implementation for$R$and$R^\dagger\$. \end{itemize} \end{document}
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