editorialbot commented 5 months ago

Submitting author: !--author-handle-->@daneschi@lrnv<!--end-editor-- Reviewers: @robmoss, @selimfirat Archive: 10.5281/zenodo.10883597

Status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/adb20d3d808e8b369e827b5d9fba277b"><img src="https://joss.theoj.org/papers/adb20d3d808e8b369e827b5d9fba277b/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/adb20d3d808e8b369e827b5d9fba277b/status.svg)](https://joss.theoj.org/papers/adb20d3d808e8b369e827b5d9fba277b)

Reviewers and authors:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

Reviewer instructions & questions

@robmoss & @selimfirat, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review. First of all you need to run this command in a separate comment to create the checklist:

@editorialbot generate my checklist

The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @lrnv know.

✨ Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest ✨

Checklists

📝 Checklist for @robmoss

📝 Checklist for @selimfirat

editorialbot commented 5 months ago

Hello humans, 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:

@editorialbot commands

For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

@editorialbot generate pdf

editorialbot commented 5 months ago

Software report:

github.com/AlDanial/cloc v 1.88  T=0.08 s (832.3 files/s, 167375.2 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          26           1011            893           2939
XML                              6              0            129           1842
Jupyter Notebook                 2              0           4069            440
Markdown                         2            124              0            416
TeX                              2             45              0            379
reStructuredText                19            158            336             93
YAML                             3             14             14             63
TOML                             1              5              1             29
DOS Batch                        1              8              1             26
Bourne Shell                     2              1              0             16
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                            65           1370           5450           6252
-------------------------------------------------------------------------------

gitinspector failed to run statistical information for the repository

editorialbot commented 5 months ago

Wordcount for paper.md is 5049

editorialbot commented 5 months ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

lrnv commented 5 months ago

👋🏼 @robmoss & @selimfirat this is the review thread for the paper. All of our communications will happen here from now on.

As a reviewer, the first step is to create a checklist for your review by entering

@editorialbot generate my checklist

as the top of a new comment in this thread.

These checklists contain the JOSS requirements. As you go over the submission, please check any items that you feel have been satisfied. The first comment in this thread also contains links to the JOSS reviewer guidelines (there : https://joss.readthedocs.io/en/latest/reviewer_guidelines.html)

The JOSS review is different from most other journals. Our goal is to work with the authors to help them meet our criteria instead of merely passing judgment on the submission. As such, the reviewers are encouraged to submit issues and pull requests on the software repository. When doing so, please mention openjournals/joss-reviews#6309 so that a link is created to this thread (and I can keep an eye on what is happening). Please also feel free to comment and ask questions on this thread. In my experience, it is better to post comments/questions/suggestions as you come across them instead of waiting until you've reviewed the entire package.

We aim for reviews to be completed within about 2-4 weeks. Please let me know if any of you require some more time. We can also use EditorialBot (our bot) to set automatic reminders if you know you'll be away for a known period of time.

Please feel free to ping me (@lrnv) if you have any questions/concerns.

editorialbot commented 5 months ago

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

OK DOIs

- None

MISSING DOIs

- 10.1016/b978-0-08-051581-6.50057-x may be a valid DOI for title: Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
- 10.2172/4390578 may be a valid DOI for title: Equation of state calculations by fast computing machines
- 10.1093/oso/9780198509936.003.0015 may be a valid DOI for title: Monte Carlo sampling methods using Markov chains and their applications
- 10.21236/ada208388 may be a valid DOI for title: Sampling-based approaches to calculating marginal densities
- 10.1561/9781601981851 may be a valid DOI for title: Graphical models, exponential families, and variational inference
- 10.1109/tpami.2020.2992934 may be a valid DOI for title: Normalizing flows: An introduction and review of current methods
- 10.1016/j.jcp.2022.111454 may be a valid DOI for title: Variational inference with NoFAS: Normalizing flow with adaptive surrogate for computationally expensive models
- 10.1615/int.j.uncertaintyquantification.2022043110 may be a valid DOI for title: AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation
- 10.1016/s0951-8320(02)00229-6 may be a valid DOI for title: Theorems and examples on high dimensional model representation
- 10.1016/0041-5553(67)90144-9 may be a valid DOI for title: On the distribution of points in a cube and the approximate evaluation of integrals

INVALID DOIs

- None

robmoss commented 5 months ago

Review checklist for @robmoss

Conflict of interest

[x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the https://github.com/desResLab/LINFA?
[x] License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@daneschi) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
[x] Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
[x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
[x] Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

[x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
[x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
[x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
[x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

lrnv commented 4 months ago

@robmoss I see your review already started, how is it going ?

@selimfirat It's been two weeks did you have the time to take a look at this submission ? If you need more time, simply tell me I can setup automatic reminders for you if you want.

robmoss commented 4 months ago

@lrnv thanks for checking in. I've made some progress, but have had to take some personal leave due to unforeseen circumstances. I will return to work next week, and continue my review. I identified a packaging issue, which is related to the paper but only applies to the software itself. Should I ask the authors to respond to this issue as part of the review process? Thanks in advance for your advice :)

lrnv commented 4 months ago

@robmoss thanks for your reply. It is definitely expected from you to raise issues that apply to the software: the subject an the content of the review should be the software, the paper is just a side-effect IMHO. So if you found bugs or problems with the software, yes you can ask the authors to fix things as part of the review process. You can ask for new features if you think they would be logically inserted into the current project, or even for more detailled documentation, refactoring of API or even refactoring of internals, if you think that some other decision would have made more sense. Sky is the limit.

robmoss commented 4 months ago

@lrnv Thanks very much for your advice. I've noted a number of small things to raise with the authors (mostly related to the few remaining unchecked items in my checklist) and will file a few issues in their repo later this week.

selimfirat commented 4 months ago

Review checklist for @selimfirat

Conflict of interest

[x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the https://github.com/desResLab/LINFA?
[x] License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@daneschi) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
[x] Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
[x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
[x] Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

[x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
[x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
[x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
[x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

editorialbot commented 4 months ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

selimfirat commented 4 months ago

@editorialbot commands

editorialbot commented 4 months ago

Hello @selimfirat, here are the things you can ask me to do:


# List all available commands
@editorialbot commands

# Get a list of all editors's GitHub handles
@editorialbot list editors

# Check the references of the paper for missing DOIs
@editorialbot check references

# Perform checks on the repository
@editorialbot check repository

# Adds a checklist for the reviewer using this command
@editorialbot generate my checklist

# Set a value for branch
@editorialbot set joss-paper as branch

# Generates the pdf paper
@editorialbot generate pdf

# Generates a LaTeX preprint file
@editorialbot generate preprint

# Get a link to the complete list of reviewers
@editorialbot list reviewers

selimfirat commented 4 months ago

@robmoss I see your review already started, how is it going ?

@selimfirat It's been two weeks did you have the time to take a look at this submission ? If you need more time, simply tell me I can setup automatic reminders for you if you want.

Hello again. I requested revisions by creating issues in the repository regarding the unchecked items: https://github.com/desResLab/LINFA/issues

Now, I am waiting until the author makes neccessary changes. Is there any other action I should take?

lrnv commented 4 months ago

@selimfirat Well done, this is great. 👍

Note that you are allowed and encouraged to also make comments and revisions requests about the code itself and not only the paper (this is the main point of JOSS reviews: to get reviewers oppinon and knowledge on the codebase). E.g., if you think the tests cases are not good enough, or if some implementation of a functionality looks clunky to you, or if you think something should be done in some other manner, like an API that does not look right etc... or, more trivially, if you find a straight up bug.

Sky is your limit.

Otherwise, everything looks good on my part :)

robmoss commented 4 months ago

@lrnv Likewise, I've created issues for each of my comments and questions, I'm now waiting for the authors to respond.

lrnv commented 3 months ago

@daneschi it has been two weeks. Would it be possible to have a status update on the issues that were raised ?

lrnv commented 3 months ago

@editorialbot commands

editorialbot commented 3 months ago

Hello @lrnv, here are the things you can ask me to do:


# List all available commands
@editorialbot commands

# Add to this issue's reviewers list
@editorialbot add @username as reviewer

# Remove from this issue's reviewers list
@editorialbot remove @username from reviewers

# Get a list of all editors's GitHub handles
@editorialbot list editors

# Assign a user as the editor of this submission
@editorialbot assign @username as editor

# Remove the editor assigned to this submission
@editorialbot remove editor

# Remind an author, a reviewer or the editor to return to a review after a 
# certain period of time (supported units days and weeks)
@editorialbot remind @reviewer in 2 weeks

# Adds a checklist for the reviewer using this command
@editorialbot generate my checklist

# Set a value for version
@editorialbot set v1.0.0 as version

# Set a value for branch
@editorialbot set joss-paper as branch

# Set a value for repository
@editorialbot set https://github.com/organization/repo as repository

# Set a value for the archive DOI
@editorialbot set set 10.5281/zenodo.6861996 as archive

# Mention the EiCs for the correct track
@editorialbot ping track-eic

# Run checks and provide information on the repository and the paper file
@editorialbot check repository

# Check the references of the paper for missing DOIs
@editorialbot check references

# Generates the pdf paper
@editorialbot generate pdf

# Recommends the submission for acceptance
@editorialbot recommend-accept

# Generates a LaTeX preprint file
@editorialbot generate preprint

# Flag submission with questionable scope
@editorialbot query scope

# Get a link to the complete list of reviewers
@editorialbot list reviewers

# Creates a post-review checklist with editor and authors tasks
@editorialbot create post-review checklist

# Open the review issue
@editorialbot start review

lrnv commented 3 months ago

@editorialbot check references

editorialbot commented 3 months ago

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

OK DOIs

- 10.1109/TPAMI.1984.4767596 is OK
- 10.1063/1.1699114 is OK
- 10.1093/biomet/57.1.97 is OK
- 10.1080/01621459.1990.10476213 is OK
- 10.1561/2200000001 is OK
- 10.1007/978-3-540-71050-9 is OK
- 10.1109/TPAMI.2020.2992934 is OK
- 10.1016/j.jcp.2022.111454 is OK
- 10.1615/Int.J.UncertaintyQuantification.2022043110 is OK
- 10.1214/aos/1176347963 is OK
- 10.18637/jss.v019.i09 is OK
- 10.1016/S0951-8320(02)00229-6 is OK
- 10.1016/j.jcp.2012.07.022 is OK
- 10.1016/0041-5553(67)90144-9 is OK

MISSING DOIs

- No DOI given, and none found for title: Normalizing flows for probabilistic modeling and i...
- No DOI given, and none found for title: Variational inference with normalizing flows
- No DOI given, and none found for title: Density estimation using real NVP
- No DOI given, and none found for title: Glow: Generative flow with invertible 1x1 convolut...
- No DOI given, and none found for title: Masked Autoregressive Flow for Density Estimation
- No DOI given, and none found for title: Improved variational inference with inverse autore...
- No DOI given, and none found for title: MADE: Masked autoencoder for distribution estimati...
- No DOI given, and none found for title: Batch normalization: Accelerating deep network tra...
- No DOI given, and none found for title: Differentially Private Normalizing Flows for Densi...
- No DOI given, and none found for title: Greedy inference with structure-exploiting lazy ma...
- No DOI given, and none found for title: Preconditioned training of normalizing flows for v...

INVALID DOIs

- None

daneschi commented 3 months ago

Hi Oskar, Just a quick update. I have addressed all issues on GitHub. I'm still working on integrating code coverage reports with GitHub Actions, and rendering python notebooks in sphinx to integrate the tutorial with the online documentation. Best, Daniele

On Mon, Mar 11, 2024 at 5:15 AM Oskar Laverny @.***> wrote:

@daneschi https://github.com/daneschi it has been two weeks. Would it be possible to have a status update on the issues that were raised ?

— Reply to this email directly, view it on GitHub https://github.com/openjournals/joss-reviews/issues/6309#issuecomment-1987941805, or unsubscribe https://github.com/notifications/unsubscribe-auth/ADJL6ENAV3GJNCRNP3JITJTYXVY45AVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTSOBXHE2DCOBQGU . You are receiving this because you were mentioned.Message ID: @.***>

lrnv commented 3 months ago

@daneschi This is great, thanks for the update. When you are done, could you ping the reviewers again so that they have a look ?

daneschi commented 3 months ago

Hi @lrnv, I have finished working on the last two issues. @robmoss and @selimfirat could you please take a look? Thank you very much for all your comments and suggestions!

On Tue, Mar 19, 2024 at 3:09 PM Oskar Laverny @.***> wrote:

@daneschi https://github.com/daneschi This is great, thanks for the update. When you are done, could you ping the reviewers again so that they have a look ?

— Reply to this email directly, view it on GitHub https://github.com/openjournals/joss-reviews/issues/6309#issuecomment-2007933739, or unsubscribe https://github.com/notifications/unsubscribe-auth/ADJL6EPQED2JRIAZAWKM4MLYZCEP3AVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMBXHEZTGNZTHE . You are receiving this because you were mentioned.Message ID: @.***>

robmoss commented 3 months ago

@lrnv I've completed my checklist. @daneschi has addressed all of my comments and has closed the relevant issues in the LINFA repository, so I have no further comments :smile:

lrnv commented 3 months ago

@editorialbot generate pdf

editorialbot commented 3 months ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

lrnv commented 3 months ago

Post-Review Checklist for Editor and Authors

Additional Author Tasks After Review is Complete

Double check authors and affiliations (including ORCIDs)
Make a release of the software with the latest changes from the review and post the version number here. This is the version that will be used in the JOSS paper.
Archive the release on Zenodo/figshare/etc and post the DOI here.
Make sure that the title and author list (including ORCIDs) in the archive match those in the JOSS paper.
Make sure that the license listed for the archive is the same as the software license.

Editor Tasks Prior to Acceptance

[x] Read the text of the paper and offer comments/corrections (as either a list or a pull request)
[x] Check that the archive title, author list, version tag, and the license are correct
[x] Set archive DOI with @editorialbot set <DOI here> as archive
[x] Set version with @editorialbot set <version here> as version
[x] Double check rendering of paper with @editorialbot generate pdf
[x] Specifically check the references with @editorialbot check references and ask author(s) to update as needed
[ ] Recommend acceptance with @editorialbot recommend-accept

lrnv commented 3 months ago

@daneschi Could you please go through the todolist I've just geenrated for you, and make a report for me ?

daneschi commented 3 months ago

@lrnv Sure, please find a short report here below. Please let me know for any further questions you may have. Thank you again for your Kind Assistance with this review!

Q1 - Double check authors and affiliations (including ORCIDs) A1 - The affiliations are correct. Only three authors have a ORCID number, i.e.:

Daniele E. Schiavazzi - 0000-0001-9205-5989 Jonathan Hauenstein - 0000-0002-9252-8210 Emma Cobian - 0000-0001-9872-6413

Q2 - Make a release of the software with the latest changes from the review and post the version number here. This is the version that will be used in the JOSS paper. A2 - The latest version has all the changes. The version number is 1.5.1. Should I create a new release on GitHub?

Q3 - Archive the release on Zenodo/figshare/etc and post the DOI here. A3 - I have archived the reslease on Zenodo ( https://zenodo.org/records/10883597) with DOI: 10.5281/zenodo.10883597

Q4 - Make sure that the title and author list (including ORCIDs) in the archive match those in the JOSS paper. A4 - Yes, the two authors list match.

Q5 - Make sure that the license listed for the archive is the same as the software license. A5 - Yes, both use a MIT licence.

On Tue, Mar 26, 2024 at 3:02 PM Oskar Laverny @.***> wrote:

@daneschi https://github.com/daneschi Could you please go through the todolist I've just geenrated for you, and make a report for me ?

— Reply to this email directly, view it on GitHub https://github.com/openjournals/joss-reviews/issues/6309#issuecomment-2021253319, or unsubscribe https://github.com/notifications/unsubscribe-auth/ADJL6EMFUURJVRSBNXWSI5TY2GZ4NAVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMRRGI2TGMZRHE . You are receiving this because you were mentioned.Message ID: @.***>

lrnv commented 3 months ago

Should I create a new release on GitHub?

No everything's alright like that, perfect, thank you very much. That was a very detailed report 🤣 !

I'll handle my part of the acceptation process first thing tomorrow.

daneschi commented 3 months ago

OK, Thanks! Best, D.

On Tue, Mar 26, 2024 at 5:39 PM Oskar Laverny @.***> wrote:

Should I create a new release on GitHub?

No everything's alright like that, perfect, thansk you very much. That was a very detailed report 🤣 !

I'll handle my part of the acceptation process first thing tomorow.

— Reply to this email directly, view it on GitHub https://github.com/openjournals/joss-reviews/issues/6309#issuecomment-2021519240, or unsubscribe https://github.com/notifications/unsubscribe-auth/ADJL6EOCUGUOVWN2TI6GMWDY2HMGXAVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMRRGUYTSMRUGA . You are receiving this because you were mentioned.Message ID: @.***>

lrnv commented 3 months ago

@editorialbot set 10.5281/zenodo.10883597 as archive

editorialbot commented 3 months ago

Done! archive is now 10.5281/zenodo.10883597

lrnv commented 3 months ago

@editorialbot set 1.5.1 as version

editorialbot commented 3 months ago

Done! version is now 1.5.1

lrnv commented 3 months ago

@daneschi The title of the zenodo archive does not match the title of the paper... There is a lacking "variational". Please fix one or the other.

daneschi commented 3 months ago

@lrnv Sorry, the title is now consistent. Best, D.

On Wed, Mar 27, 2024 at 4:49 AM Oskar Laverny @.***> wrote:

@daneschi https://github.com/daneschi The title of the zenodo archive does not match the title of the paper... There is a lacking "variational". Please fix one or the other.

— Reply to this email directly, view it on GitHub https://github.com/openjournals/joss-reviews/issues/6309#issuecomment-2022230511, or unsubscribe https://github.com/notifications/unsubscribe-auth/ADJL6EKERLXH7WZYH6S5HO3Y2J2XRAVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMRSGIZTANJRGE . You are receiving this because you were mentioned.Message ID: @.***>

lrnv commented 3 months ago

@editorialbot generate pdf

lrnv commented 3 months ago

@editorialbot check references

editorialbot commented 3 months ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

editorialbot commented 3 months ago

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

OK DOIs

- 10.1109/TPAMI.1984.4767596 is OK
- 10.1063/1.1699114 is OK
- 10.1093/biomet/57.1.97 is OK
- 10.1080/01621459.1990.10476213 is OK
- 10.1561/2200000001 is OK
- 10.1007/978-3-540-71050-9 is OK
- 10.1109/TPAMI.2020.2992934 is OK
- 10.1016/j.jcp.2022.111454 is OK
- 10.1615/Int.J.UncertaintyQuantification.2022043110 is OK
- 10.1214/aos/1176347963 is OK
- 10.18637/jss.v019.i09 is OK
- 10.1016/S0951-8320(02)00229-6 is OK
- 10.1016/j.jcp.2012.07.022 is OK
- 10.1016/0041-5553(67)90144-9 is OK
- 10.21105/joss.05428 is OK

MISSING DOIs

- No DOI given, and none found for title: Normalizing flows for probabilistic modeling and i...
- No DOI given, and none found for title: Variational inference with normalizing flows
- No DOI given, and none found for title: Density estimation using real NVP
- No DOI given, and none found for title: Glow: Generative flow with invertible 1x1 convolut...
- No DOI given, and none found for title: Masked Autoregressive Flow for Density Estimation
- No DOI given, and none found for title: Improved variational inference with inverse autore...
- No DOI given, and none found for title: MADE: Masked autoencoder for distribution estimati...
- No DOI given, and none found for title: Batch normalization: Accelerating deep network tra...
- No DOI given, and none found for title: Differentially Private Normalizing Flows for Densi...
- No DOI given, and none found for title: Greedy inference with structure-exploiting lazy ma...
- No DOI given, and none found for title: Preconditioned training of normalizing flows for v...
- 10.7717/peerj-cs.1516 may be a valid DOI for title: PyMC: a modern, and comprehensive probabilistic pr...
- No DOI given, and none found for title: Bayespy: variational Bayesian inference in Python
- No DOI given, and none found for title: Pyro: Deep universal probabilistic programming

INVALID DOIs

- None

lrnv commented 3 months ago

@editorialbot recommend-accept

editorialbot commented 3 months ago

Attempting dry run of processing paper acceptance...

editorialbot commented 3 months ago

The paper's PDF and metadata files generation produced some warnings that could prevent the final paper from being published. Please fix them before the end of the review process.

\symbfit{z}\in\symbfit{\mathcal{Z}}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace


        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}\in\symbfit{\mathcal{X}}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{\varepsilon}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

^{d}\times \symbfit{\Lambda} \to \mathbb
                   ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

q_{0}(\symbfit{z}_{0})
              ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

q_{K}(\symbfit{z}_{K})
              ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p(\symbfit{z}|\symbfit{x})
          ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace


        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{\lambda}\in\symbfit{\Lambda}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

q_{K}(\symbfit{z}_{K})\approx p(\symbfit
              ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}\in\mathcal{\symbfit{X}}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

l_{\symbfit{z}}(\symbfit{x})
           ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{\varepsilon}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p(\symbfit{z})
          ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

q_K(\symbfit{z})
            ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p(\symbfit{z}|\symbfit{x})
          ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\log p(\symbfit{x})
               ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

egin{split}
                   ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{z} = (z_{1},z_{2},\dots,z_{d})
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\widehat{\symbfit{z}}_{d'+1:d} = \symbfi
                 ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{\mu} = f_{\mu}(\symbfit{z}_{1:d
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{\alpha} = f_{\alpha}(\symbfit{z
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{f}: \symbfit{\mathcal{Z}} \to \
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{z} = (z_1, z_2, \cdots, z_d)^T 
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

x_m)^T \in \symbfit{\mathcal{X}}
                   ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit x = \{\symbfit x_i\}_{i=1}^n \s
         ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit z
         ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p(\symbfit z\vert \symbfit x)\propto \el
           ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p(\symbfit z)
           ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{\lambda}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p(\symbfit x, \symbfit z_K)
           ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p(\symbfit x\vert\symbfit z_K)\,p(\symbf
           ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

=\ell_{\symbfit z_K}(\symbfit{x},\symbfi
                ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{f}(\symbfit{z})
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{f}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\widehat{\symbfit{f}}: \symbfit{\mathcal
                 ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{w} \in \symbfit{\mathcal{W}}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{w}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\widehat{\symbfit{f}}
                 ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{z}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p_k(\symbfit{z},\symbfit{x}) = p^{t_k}(\
            ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace


                   ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p^{t_{k}}(\symbfit{z},\symbfit{x})
                  ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p(\symbfit{z},\symbfit{x})
          ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace


           ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace


        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}_{0} \sim \mathcal{N}(0,\symb
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{z}^{*} = (3, 5)^T
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}^{*} = f(\symbfit z^{*})=(7.9
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit z
         ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

p(\symbfit z)
           ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace


          ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

g_i(\symbfit{r}) = (2\cdot |2\,a_{i} - 1
            ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{A}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace


        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{z}^{*} = (2.75,
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

 g^{-1}(g(\symbfit z^*) + \symbfit v\,t)
                   ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}^{*} = f(\symbfit{z}^{*}) = f
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit v = (1,-1,1,-1,1)^T
         ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit A
         ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x} = \symbfit{x}^{*} + 0.01\cdo
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}_{0} \sim \mathcal{N}(0,\symb
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}^{*}=(x^{*}_{1},x^{*}_{2},x^{
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit{x}^{*}
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

N(\symbfit\mu, \symbfit\Sigma)
          ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\mu=(f_{1}(\symbfit{z}^{*}),f_{2}(\symbf
                   ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

\symbfit\Sigma
        ^
unexpected control sequence \symbfit
expecting "%", "\\label", "\\tag", "\\nonumber" or whitespace

editorialbot commented 3 months ago

:warning: Error preparing paper acceptance. The generated XML metadata file is invalid.

ID figU003Atrivial already defined

editorialbot commented 3 months ago

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

OK DOIs

- 10.1109/TPAMI.1984.4767596 is OK
- 10.1063/1.1699114 is OK
- 10.1093/biomet/57.1.97 is OK
- 10.1080/01621459.1990.10476213 is OK
- 10.1561/2200000001 is OK
- 10.1007/978-3-540-71050-9 is OK
- 10.1109/TPAMI.2020.2992934 is OK
- 10.1016/j.jcp.2022.111454 is OK
- 10.1615/Int.J.UncertaintyQuantification.2022043110 is OK
- 10.1214/aos/1176347963 is OK
- 10.18637/jss.v019.i09 is OK
- 10.1016/S0951-8320(02)00229-6 is OK
- 10.1016/j.jcp.2012.07.022 is OK
- 10.1016/0041-5553(67)90144-9 is OK
- 10.21105/joss.05428 is OK

MISSING DOIs

- No DOI given, and none found for title: Normalizing flows for probabilistic modeling and i...
- No DOI given, and none found for title: Variational inference with normalizing flows
- No DOI given, and none found for title: Density estimation using real NVP
- No DOI given, and none found for title: Glow: Generative flow with invertible 1x1 convolut...
- No DOI given, and none found for title: Masked Autoregressive Flow for Density Estimation
- No DOI given, and none found for title: Improved variational inference with inverse autore...
- No DOI given, and none found for title: MADE: Masked autoencoder for distribution estimati...
- No DOI given, and none found for title: Batch normalization: Accelerating deep network tra...
- No DOI given, and none found for title: Differentially Private Normalizing Flows for Densi...
- No DOI given, and none found for title: Greedy inference with structure-exploiting lazy ma...
- No DOI given, and none found for title: Preconditioned training of normalizing flows for v...
- 10.7717/peerj-cs.1516 may be a valid DOI for title: PyMC: a modern, and comprehensive probabilistic pr...
- No DOI given, and none found for title: Bayespy: variational Bayesian inference in Python
- No DOI given, and none found for title: Pyro: Deep universal probabilistic programming

INVALID DOIs

- None

daneschi commented 3 months ago

Hi @lrnv, should I fix these issues? Can I change the version when submitting to the repo? Do I need to also update the zip file on Zenodo? Thanks! D.

On Wed, Mar 27, 2024 at 9:47 AM The Open Journals editorial robot < @.***> wrote:

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

OK DOIs

10.1109/TPAMI.1984.4767596 is OK

10.1063/1.1699114 is OK

10.1093/biomet/57.1.97 is OK

10.1080/01621459.1990.10476213 is OK

10.1561/2200000001 is OK

10.1007/978-3-540-71050-9 is OK

10.1109/TPAMI.2020.2992934 is OK

10.1016/j.jcp.2022.111454 is OK

10.1615/Int.J.UncertaintyQuantification.2022043110 is OK

10.1214/aos/1176347963 is OK

10.18637/jss.v019.i09 is OK

10.1016/S0951-8320(02)00229-6 is OK

10.1016/j.jcp.2012.07.022 is OK

10.1016/0041-5553(67)90144-9 is OK

10.21105/joss.05428 is OK

MISSING DOIs

No DOI given, and none found for title: Normalizing flows for probabilistic modeling and i...

No DOI given, and none found for title: Variational inference with normalizing flows

No DOI given, and none found for title: Density estimation using real NVP

No DOI given, and none found for title: Glow: Generative flow with invertible 1x1 convolut...

No DOI given, and none found for title: Masked Autoregressive Flow for Density Estimation

No DOI given, and none found for title: Improved variational inference with inverse autore...

No DOI given, and none found for title: MADE: Masked autoencoder for distribution estimati...

No DOI given, and none found for title: Batch normalization: Accelerating deep network tra...

No DOI given, and none found for title: Differentially Private Normalizing Flows for Densi...

No DOI given, and none found for title: Greedy inference with structure-exploiting lazy ma...

No DOI given, and none found for title: Preconditioned training of normalizing flows for v...

10.7717/peerj-cs.1516 may be a valid DOI for title: PyMC: a modern, and comprehensive probabilistic pr...

No DOI given, and none found for title: Bayespy: variational Bayesian inference in Python

No DOI given, and none found for title: Pyro: Deep universal probabilistic programming

INVALID DOIs

None

— Reply to this email directly, view it on GitHub https://github.com/openjournals/joss-reviews/issues/6309#issuecomment-2022815138, or unsubscribe https://github.com/notifications/unsubscribe-auth/ADJL6EN546JQDSAFJKV2R43Y2K5WRAVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMRSHAYTKMJTHA . You are receiving this because you were mentioned.Message ID: @.***>

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[REVIEW]: LINFA: a Python library for variational inference with normalizing flow and annealing #6309

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