
Experiments in Handwriting with a Neural Network - swannodette
http://distill.pub/2016/handwriting/
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ludwigschubert
This is incredible important research. There are fields in which adoption of
ML techniques is dependent on it being explainable and inspectable to
stakeholders, e.g. in certain health care, policy or finance applications.

There is work being done on explaining non-linear models, such as LIME [1],
but much more is needed. At a recent d3 meetup the topic was discussed but we
primarily noted its importance. Notes at [2].

[1] [https://github.com/marcotcr/lime](https://github.com/marcotcr/lime) [2]
[https://docs.google.com/document/d/1o-DO65PEZShLuadyRd35PsTJ...](https://docs.google.com/document/d/1o-DO65PEZShLuadyRd35PsTJ_XMi62Nhb1XOVQu2sUQ/edit)

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shancarter
Me and the other authors of the post will be around if anyone has any
questions.

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inlineint
How much computing power/time did it take to train the model? Had any
hyperparameters optimization been done?

Sorry if I missed the reference that has this information, but I think that
these numbers are important in any deep learning experiment because they allow
the readers to evaluate applicability of described methods to their problems.

~~~
shancarter
This post has more details about the model:
[http://blog.otoro.net/2015/12/12/handwriting-generation-
demo...](http://blog.otoro.net/2015/12/12/handwriting-generation-demo-in-
tensorflow/)

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colah3
Note that the contribution of this article is techniques for visualizing
models, not the novel itself.

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ludwigschubert
In "Examining the Internals of the Model" it could be interesting to show an
overview activation map that sums over the absolute activation of all the
examples—to highlight which cells activate on all examples—and one that is
colored by variance of activation across examples—to show which cells
influence the character/differences in writing.

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nl
Nice! Is it trained on Latin character-based hand writing only, or can it also
predict other charactersets?

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colah3
Latin character only. It was trained on the IAM Handwriting database [1],
which is all English handwriting.

[1] [http://www.fki.inf.unibe.ch/databases/iam-handwriting-
databa...](http://www.fki.inf.unibe.ch/databases/iam-handwriting-database)

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Qwertystop
Quite interesting to see the inspection of the model.

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devoply
We're slowly coming to an era where everything can be easily forged.

~~~
AstralStorm
Except digital signatures. Those are still hard and much easier to steal or
phish than crack.

