JJGO/hyperlight

FCN.output.bias = learnable parameters \theta_0 ?

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Hi @JJGO ,

thanks a lot for sharing the code.

In chapter 4 Output Encoding part of the paper, it mentioned the method introduces a set of learnable parameters \theta_0 and uses the hypernetwork predictions as additive changes.

Does \theta_0 correspond to the bias of the output layer of the FCN, which is also called independent weights in the class functions?

Thank you!