[PRE REVIEW]: High-performance neural population dynamics modeling enabled by scalable computational infrastructure

[editorialbot]

Submitting author: @a9p (Aashish Patel)
Repository: https:/TNEL-UCSD/autolfads-deploy
Branch with paper.md (empty if default branch):
Version: v1.0.0
Editor: @emdupre
Reviewers: @richford, @tachukao
Managing EiC: Kevin M. Moerman

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Author instructions

Thanks for submitting your paper to JOSS @a9p. Currently, there isn't a JOSS editor assigned to your paper.

@a9p if you have any suggestions for potential reviewers then please mention them here in this thread (without tagging them with an @). In addition, this list of people have already agreed to review for JOSS and may be suitable for this submission (please start at the bottom of the list).

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Software report:

github.com/AlDanial/cloc v 1.88  T=1.14 s (893.1 files/s, 300048.6 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
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YAML                           956            816           3611         332355
Python                          10            208            286           1386
Markdown                        29            441              0           1116
Bourne Shell                    12            133            200            496
TeX                              1             14              0            128
make                             5             25             14             58
JSON                             3              0              0             51
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SUM:                          1016           1637           4111         335590
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gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 2023

[editorialbot]

⚠️ An error happened when generating the pdf.

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- None

MISSING DOIs

- 10.1038/nn.3776 may be a valid DOI for title: Dimensionality reduction for large-scale neural recordings
- 10.1101/2021.01.13.426570 may be a valid DOI for title: A large-scale neural network training framework for generalized estimation of single-trial population dynamics

INVALID DOIs

- None

[a9p]

@editorialbot generate pdf

[editorialbot]

⚠️ An error happened when generating the pdf.

[a9p]

@editorialbot generate pdf

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[Kevin-Mattheus-Moerman]

@a9p thanks for this submission. I will be looking for a handling editor. Unfortunately all editors in this domain are currently busy handling other submissions. Hence I have waitlisted this submission at the moment. We will assign an editor once one becomes available. Thanks for your patience.

[a9p]

Sounds good, thank you for the update!

[Kevin-Mattheus-Moerman]

@emdupre does this submission look like something you could handle as editor? You do seem to be handling several other submissions already, so do let me know if you prefer to leave this waitlisted for the moment, or if we can assign it to you now (and that perhaps you'd get to it whenever you have time). Thanks.

[emdupre]

Thanks for the invitation, @Kevin-Mattheus-Moerman ! I am already managing two submissions, but I think this is well-aligned with my expertise so I'm happy to take this on. I'll try to get it started quickly.

[Kevin-Mattheus-Moerman]

@editorialbot assign @emdupre as editor

[editorialbot]

Assigned! @emdupre is now the editor

[emdupre]

👋 Hi @a9p, and thank you for your submission to JOSS !

If you have any suggestions for potential reviewers, please let me know by listing their names or GitHub handles (without the @ character, so they don't receive a notification) here.

[emdupre]

👋 Hi @cellistigs, @dghoshal-lbl, @mattgolub, @lyprince,

Would you be willing to review High-performance neural population dynamics modeling enabled by scalable computational infrastructure for JOSS (the Journal of Open Source Software)?

You can learn more about reviewing for JOSS -- including our conflict of interest policy -- here.

The review takes place on GitHub and focuses on the software and this short paper:
https:/openjournals/joss-papers/blob/joss.04892/joss.04892/10.21105.joss.04892.pdf

If you're available to review this work, please let me know and I'll add you as a reviewer. Once I have sufficient reviewers I'll open a dedicated review issue.

Thank you !

[mattgolub]

Hi Elizabeth, I wish I could participate here, but I have just taken on way too much recently. I wouldn't be able to give this the attention it deserves. So I must respectfully decline. Best, Matt

…

-- Matthew Golub, PhD Assistant Professor Paul G. Allen School for Computer Science & Engineering University of Washington homes.cs.washington.edu/~mgolub

On Wed, Nov 9, 2022 at 5:20 PM Elizabeth DuPre ***@***.***> wrote: 👋 Hi @cellistigs <https:/cellistigs>, @dghoshal-lbl <https:/dghoshal-lbl>, @mattgolub <https:/mattgolub>, @lyprince <https:/lyprince>, Would you be willing to review *High-performance neural population dynamics modeling enabled by scalable computational infrastructure* for JOSS (the Journal of Open Source Software) <https://joss.theoj.org/>? You can learn more about reviewing for JOSS -- including our conflict of interest policy -- here <https://joss.readthedocs.io/en/latest/reviewer_guidelines.html>. The review takes place on GitHub and focuses on the software <https:/TNEL-UCSD/autolfads-deploy> and this short paper: https:/openjournals/joss-papers/blob/joss.04892/joss.04892/10.21105.joss.04892.pdf If you're available to review this work, please let me know and I'll add you as a reviewer. Once I have sufficient reviewers I'll open a dedicated review issue. Thank you ! — Reply to this email directly, view it on GitHub <#4892 (comment)>, or unsubscribe <https:/notifications/unsubscribe-auth/AG4KOBUPYFSV7WEGRMQ5IFLWHRETXANCNFSM6AAAAAARRVXGZI> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[emdupre]

Thank you for letting me know, @mattgolub ! I appreciate your response.

[a9p]

Hi @emdupre, thank you for keeping up with this! Chatting with the team, we think the following would be capable reviewers in addition to the ones you suggested:

• Guillaume Hennequin (ghennequin)
• Lea Duncker (leaduncker)
• Juan Gallego lab
• Andreas Tolias lab

[emdupre]

Thank you for the suggestions, @a9p !

I've also reached out to a few potential reviewers over email ; I will, though, send out new invitations after the holiday (tomorrow and Friday here in the US).

[emdupre]

👋 Hi @ghennequin, @shrinandj, @richford, @rabernat,

Would you be willing to review High-performance neural population dynamics modeling enabled by scalable computational infrastructure for JOSS (the Journal of Open Source Software)?

This submission aims to provide container-native access for training AutoLFADS models across unmanaged (using Ray) and managed (using KubeFlow and Kubernetes) compute clusters.

You can learn more about reviewing for JOSS -- including our conflict of interest policy -- here.

The review takes place on GitHub and focuses on the software and this short paper:
https:/openjournals/joss-papers/blob/joss.04892/joss.04892/10.21105.joss.04892.pdf

If you're available to review this work, please let me know and I'll add you as a reviewer. Once I have sufficient reviewers I'll open a dedicated review issue.

Thank you !

[richford]

Hi @emdupre, I can review this submission. Thanks for reaching out.

[rabernat]

Sorry but I cannot commit to this review at this time.

[emdupre]

Thank you, @richford and @rabernat, for letting me know ! I appreciate your responses.

@richford, I'll go ahead and add you on the submission now while I recruit additional reviewers 🚀

[emdupre]

@editorialbot add @richford to reviewers

[editorialbot]

@richford added to the reviewers list!

[emdupre]

👋 Hi @tachukao, following up on our email exchange, I'll add you as a reviewer on this submission. Please let me know if you have any remaining questions or concerns before I start the review process !

[tachukao]

Hi @emdupre, happy to review. Thanks for reaching out!

[emdupre]

Perfect, thank you for confirming @tachukao !

I'll add you as a reviewer now and go ahead and open the review issue for you and @richford ! 🚀

[emdupre]

@editorialbot add @tachukao to reviewers

[editorialbot]

@tachukao added to the reviewers list!

[emdupre]

@editorialbot start review

[editorialbot]

OK, I've started the review over in #5023.