
Show HN: Interactive deep convnet visualization for Keras and Tensorflow - dbranes
https://jakebian.github.io/quiver/
======
visarga
That looks useful for getting insights into what is happening in a NN.

What is it visualizing in a convolutional layer, does it average all the
channels, or select just one?

~~~
taliesinb
As slick as this kind of thing looks, I don't think it _does_ help much to see
raw filters on an image-by-image basis. The kind of insights that I think are
more important are the abstract ones, like the recent paper about universal
adversarial perturbations and the geometry of the decision boundary.

Visualizations can help, but more in the sense of rapidly iterating through
bespoke visualizations to generate and test hypotheses. And to do that
efficiently you don't need a slick tool that does one kind of visualization,
you need a slick 'grammar' to efficiently build new visualizations with, Bret
Victor style.

~~~
TFortunato
Do you have a link to the paper you are referring to?

~~~
taliesinb
[https://arxiv.org/pdf/1610.08401v1.pdf](https://arxiv.org/pdf/1610.08401v1.pdf)

Sorry, I have to ask.. any relation to Dan Fortunato? Maybe that's just a
really common name in Boston.

~~~
d_fortunato
No relation... I think Fortunato is pretty rare. Also: hey Tali! :)

~~~
ReelDFortunato
No... He was referring to me! I'm from Boston...

------
joelthelion
It would be nice to also have a way to visualize filters (eg.
[https://blog.keras.io/how-convolutional-neural-networks-
see-...](https://blog.keras.io/how-convolutional-neural-networks-see-the-
world.html))

------
SynapticSelf
I created an account just to say that this looks really fantastic. Thanks for
creating this! I'm looking forward to steady improvements in neural network
tooling, and it's people like yourself that keep that train moving forward.

------
Radim
License file missing, but setup.py seems to imply MIT.

