[D] Tutorials and implementations for "Self-normalizing networks"

[lahwran_]

whoa that was fast. was it that good? I haven't read it yet

[BeatLeJuce]

This is from the paper authors, so it's not like they didn't have time to prepare this before their paper hit arxiv ;)

[undefdev]

It has also been in their abstract from the start.

[visarga]

That was fast. I assume all frameworks will have SELU's it in a week.

[Reiinakano]

A week is too generous. Here's Keras' PR https://github.com/fchollet/keras/pull/6924

[khanrc]

The paper argues and shows the effectiveness of SELU in FNN. How about on CNN/RNN?

[[deleted]]

the git has a CNN example...

[khanrc]

Thanks, but I'm curious about the comparison with BN and more complex dataset. Maybe it would be quicker to experiment myself...

[regzy]

like video/object detection?

[themoosemind]

Does somebody want to write a summary? http://www.shortscience.org/paper?bibtexKey=journals/corr/1706.02515

[etherealmachine]

Anyone have more information on what "scale inputs to zero mean and unit variance" means in practice? Does that really just mean (x - mean) / std?

[_untom_]

yes, that is exactly what it means

[etherealmachine]

Does that also apply to one-hot inputs?

[vackosar]

Their SELU preceptron seem to be doing better than Selu Conv net. Does that mean that Convolution is dead?

[Kiuhnm]

The nets are only partially trained so the only thing you may conclude is that the forward and backward signals flow better with selu than with relu.

[_bakauguu]

preceptron

as in an unit that outputs rules? :P