On Wed, 31 May 2023, 22:41 Robert Kern, <robert.k...@gmail.com> wrote:
> Not sure anyone really uses tanh for serious work. > At the risk of derailing the discussion, the case I can think of (but kind of niche) is using neural networks to approximate differential equations. Then you need non linearities in the gradients everywhere. I have also experimented with porting a few small networks and other ML models to numpy by hand to make it easier to deploy. But then, performance in my use case wasn't crítical. > >
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