# Implementation of Spectral Normalization for Machine Learning

**URL:** <https://discourse.julialang.org/t/implementation-of-spectral-normalization-for-machine-learning/76074>\
**Category:** General Usage\
**Created:** [February 9, 2022, 12:39pm UTC](https://discourse.julialang.org/t/implementation-of-spectral-normalization-for-machine-learning/76074 "2022-02-09T12:39:09Z")\
**Posts on this page:** 1\
**Showing post:** 5

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**Author:** ![goerch](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/goerch/32/29122_2.png) [@goerch](https://discourse.julialang.org/u/goerch)\
**Post date:** [February 9, 2022, 1:36pm UTC](https://discourse.julialang.org/t/implementation-of-spectral-normalization-for-machine-learning/76074/5 "2022-02-09T13:36:35Z")

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> [@baggepinnen](#):
>
> The norm you’re using is called `opnorm` in Julia, perhaps this function is differentiable

Interesting. This reminds me of [this thread](https://discourse.julialang.org/t/automatic-differentiation-of-complex-matrix-fails/75733) where I learned that at least differentiation of real `svd` seems supported by Zygote?

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