I'm not against this idea; but what's the point? Clearly it's to provide some benefit to efficient implementation of particular procedures in Quil, but it'd be nice to see some detail of that, and how this might matter outside of Quil.
This is an awesome paper; great work! :)
Wow, from one-way QC to AI! :)
I think this thread has reached it's end.
I've locked further comments, and I hope that the quantum computing community can thoughtfully find an approach to language that is inclusive to all and recognises the diverse background of all researchers, current and future.
I direct your attention to our [moderation policy](https://scirate.com/moderation).
I've moderated a few comments on this post because I believe it has gone past useful discussion, and I'll continue to remove comments that I believe don't add anything of substantial value.
Awesome, my email is firstname.lastname@example.org :)
Nice work! Are you planning on sharing the code you wrote to run this in the IBM quantum experience system?
This is interesting work.
Did the authors happen to make their code available? I think there might be a few other fun experiments to run, and in particular I'd be interested to know how to use this framework for picking a network that does best at _both_ tasks (from the experiments section). That is, supposing I want to be good at recognising small digits _and_ large digits, should I just have a large number of channels through-out?
I also don't feel completely comfortable with the arguments around page 11 about the correlations expected in natural and face images. Even in natural images (where I'm going to concern myself with looking for object) there's going to be high correlation between either side of the picture. I.e. the left half of a dog is highly correlated with the right half of it ...? Am I missing something here?
I feel that while the proliferation of GUNs is unquestionable a good idea, there are many unsupervised networks out there that might use this technology in dangerous ways. Do you think Indifferential-Privacy networks are the answer? Also I fear that the extremist binary networks should be banned entirely from this field. Interested in your thoughts; thanks!
This is a cool paper!
I don't even really see the point of a journal. Maybe we could adapt SciRate to have a little collection of longer reviews/editorials/etc associated to each article (like comments).
What do you think a journal would offer over SciRate itself? I.e. if the potential paper reviewers would just instead post their thoughts as these "reviews" here, then you could just watch for new reviews, and bypass any publishing process and so on.
Great institute name ...
Note that it's not possible to submit papers to SciRate directly; this site simply aggregates information from other sites. However, I've added an issue relating to potentially marking withdrawn papers - https://github.com/scirate/scirate/issues/318.
Relevant: http://algorithmicassertions.com/quantum/2015/08/01/Checking-a-Claimed-BQP-NP-Algorithm.html & https://github.com/Strilanc/qbp_np_younes_test
You can always make suggestions on the GitHub project pages' [issue list](https://github.com/scirate/scirate/issues). I've included this one here: https://github.com/scirate/scirate/issues/315.
There's some code for this here: https://github.com/ryankiros/skip-thoughts
The system works. Machine learners hate him.
I took the liberty of uploading the IPython notebook as a github [gist](https://gist.github.com), so it's viewable [here](http://nbviewer.ipython.org/urls/gist.githubusercontent.com/silky/b14fa42c6d5475a3a724/raw/887c19fb04581f1a33f9d03370e4b7b3a33c2ea8/ferrie_kueng_bayes_est_fid.ipynb).
I'm pretty sure this first author was just entirely made up ...; but is the error in the name intentional? Weird!
For fun, I created the following IPython notebook replicating the graphs in this paper: http://nbviewer.ipython.org/github/silky/paper_workings/blob/master/arxiv_1403.0069.ipynb.
(Actually, it's on the sagemath cloud, where if you have an account you can probably edit it - https://cloud.sagemath.com/dad98beb-ba53-4b68-bcdf-12f757360193/port/60276/)