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[PRE REVIEW]: PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs #5634
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Hello human, I'm @editorialbot, a robot that can help you with some common editorial tasks. For a list of things I can do to help you, just type:
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@editorialbot invite @jni as editor |
Invitation to edit this submission sent! |
List of potential reviewers working on graphs and AI:
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Hello @diningphil, here are the things you can ask me to do:
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Apologies @gkthiruvathukal, I am travelling ~non-stop till October so I really don't have the bandwidth right now and must decline. 🙏 |
@editorialbot invite @adonath as editor |
Invitation to edit this submission sent! |
I believe @adonath is on parental leave (judging from his status on Github). Do you think it would be good to invite another editor for the submission? Many thanks, |
@editorialbot assign me as editor |
Assigned! @arfon is now the editor |
👋 @idoby @jkbren @nidhog would any of you be willing to review this submission for JOSS? The submission under consideration is PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs The review process at JOSS is unique: it takes place in a GitHub issue, is open, and author-reviewer-editor conversations are encouraged. You can learn more about the process in these guidelines: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html Based on your experience, we think you might be able to provide a great review of this submission. Please let me know if you think you can help us out! Many thanks |
Sure, this seems interesting and very relevant. |
Fantastic, thanks @idoby! I'll go ahead and add you as a reviewer now but won't actually start the review thread until I have a second reviewer lined up. Hopefully this won't be too long. |
@editorialbot add @idoby as reviewer |
@idoby added to the reviewers list! |
👋 @sepandhaghighi @matteocao – would either of you be willing to review this submission for JOSS? The submission under consideration is PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs. The review process at JOSS is unique: it takes place in a GitHub issue, is open, and author-reviewer-editor conversations are encouraged. You can learn more about the process in these guidelines: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html Based on your experience, we think you might be able to provide a great review of this submission. Please let me know if you think you can help us out! Many thanks |
Hi SH |
@editorialbot add @sepandhaghighi as reviewer Thanks @sepandhaghighi! |
@sepandhaghighi added to the reviewers list! |
@editorialbot start review |
OK, I've started the review over in #5713. |
@idoby, @sepandhaghighi – see you over in #5713 where the review will actually take place. |
Submitting author: @diningphil (Federico Errica)
Repository: https://github.com/diningphil/PyDGN/
Branch with paper.md (empty if default branch): paper
Version: v1.3.1
Editor: @arfon
Reviewers: @idoby, @sepandhaghighi
Managing EiC: George K. Thiruvathukal
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