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[REVIEW]: iTensor: An R package for independent component analysis-based matrix/tensor decomposition #5496

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editorialbot opened this issue May 29, 2023 · 54 comments
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accepted Dockerfile published Papers published in JOSS R recommend-accept Papers recommended for acceptance in JOSS. review TeX Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning

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editorialbot commented May 29, 2023

Submitting author: @kokitsuyuzaki (Koki Tsuyuzaki)
Repository: https://github.com/rikenbit/iTensor
Branch with paper.md (empty if default branch):
Version: v1.0.3
Editor: @osorensen
Reviewers: @ritika-giri, @devarops
Archive: 10.5281/zenodo.8080600

Status

status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/cffccfbad7fc8bda9395e429c3c6f35d"><img src="https://joss.theoj.org/papers/cffccfbad7fc8bda9395e429c3c6f35d/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/cffccfbad7fc8bda9395e429c3c6f35d/status.svg)](https://joss.theoj.org/papers/cffccfbad7fc8bda9395e429c3c6f35d)

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

@ritika-giri & @devarops, 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 @osorensen 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 @devarops

📝 Checklist for @ritika-giri

@editorialbot editorialbot added Dockerfile R review TeX Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning waitlisted Submissions in the JOSS backlog due to reduced service mode. labels May 29, 2023
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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

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Software report:

github.com/AlDanial/cloc v 1.88  T=0.02 s (1357.0 files/s, 196210.6 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
R                               13            168            630           1970
TeX                              2             47             50            308
Markdown                         7             66              0            229
Rmd                              3             89            175             95
YAML                             1             12             13             45
Dockerfile                       1              1              2              4
-------------------------------------------------------------------------------
SUM:                            27            383            870           2651
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

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Wordcount for paper.md is 725

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

OK DOIs

- None

MISSING DOIs

- 10.7551/mitpress/7011.003.0009 may be a valid DOI for title: An information-maximization approach to blind separation and blind deconvolution
- 10.1162/089976699300016719 may be a valid DOI for title: Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources
- 10.1109/72.761722 may be a valid DOI for title: Fast and robust fixed-point algorithms for independent component analysis
- 10.1049/ip-f-2.1993.0054 may be a valid DOI for title: Blind beamforming for non-gaussian signals
- 10.1007/978-3-642-15995-4_21 may be a valid DOI for title: Auxiliary-Function-Based Independent Component Analysis for Super-Gaussian Sources
- 10.1186/1471-2105-13-24 may be a valid DOI for title: Independent Principal Component Analysis for biologically meaningful dimension reduction of large biological data sets
- 10.1109/31.76486 may be a valid DOI for title: Indeterminacy and identifiability of blind identification
- 10.1109/icassp.1989.266878 may be a valid DOI for title: Source separation using higher order moments
- 10.1109/ijcnn.1999.831077 may be a valid DOI for title: MICA: Multimodal independent component analysis
- 10.1016/j.neuroimage.2008.10.057 may be a valid DOI for title: A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data
- 10.1016/j.sigpro.2022.108457 may be a valid DOI for title: CorrIndex: a permutation invariant performance index
- 10.1109/memb.2006.1607672 may be a valid DOI for title: Unmixing fMRI with Independent Component Analysis
- 10.1038/nbt.2859 may be a valid DOI for title: The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
- 10.3389/fnins.2013.00267 may be a valid DOI for title: MEG and EEG data analysis with MNE-Python
- 10.1371/journal.pone.0270556 may be a valid DOI for title: Comparing the reliability of different ICA algorithms for fMRI analysis
- 10.1109/spmb.2016.7846858 may be a valid DOI for title: Applying fully tensorial ICA to fMRI data

INVALID DOIs

- None

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

@devarops
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devarops commented May 29, 2023

Review checklist for @devarops

Conflict of interest

  • 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

General checks

  • Repository: Is the source code for this software available at the https://github.com/rikenbit/iTensor?
  • License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
  • Contribution and authorship: Has the submitting author (@kokitsuyuzaki) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
  • Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
  • 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.
  • Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
  • 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

Documentation

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

  • Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
  • 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?
  • State of the field: Do the authors describe how this software compares to other commonly-used packages?
  • Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
  • 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?

Documentation

Testing

docker run --rm -it -v ${PWD}:/workdir ghcr.io/rikenbit/itensor bash
cd /workdir
Rscript -e "devtools::test(stop_on_failure = TRUE)"
ℹ Testing iTensor
✔ | F W S  OK | Context
✔ |        24 | GroupICA [0.3s]                                                                                   
✔ |        49 | ICA [0.6s]                                                                                        
✔ |       132 | ICA2 [51.0s]                                                                                      
✔ |        29 | MICA [0.6s]                                                                                       
✔ |        26 | MultilinearICA [1.0s]                                                                             

══ Results ═══════════════════════════════════════════════════════════════════════════════════════════════════════
Duration: 53.4 s

[ FAIL 0 | WARN 0 | SKIP 0 | PASS 260 ]

Coverage

docker run --rm -it -v ${PWD}:/workdir ghcr.io/rikenbit/itensor bash
cd /workdir
Rscript -e "install.packages(c('covr','DT','htmltools'))"
Rscript tests/testthat/coverage.R
iTensor Coverage: 35.80%
R/CorrIndex.R: 0.00%
R/toyModel.R: 0.00%
R/GroupICA.R: 18.14%
R/ICA2.R: 26.93%
R/ICA.R: 62.26%
R/MICA.R: 97.08%
R/MultilinearICA.R: 97.50%

image

tests/testthat/coverage.R:

library(covr)
cov <- package_coverage()
print(cov)
zero_coverage(cov)
report(cov, file = file.path("/workdir/tests/coverage-report.html"), browse = FALSE)

@ritika-giri
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ritika-giri commented May 29, 2023

Review checklist for @ritika-giri

Conflict of interest

  • 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

General checks

  • Repository: Is the source code for this software available at the https://github.com/rikenbit/iTensor?
  • License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
  • Contribution and authorship: Has the submitting author (@kokitsuyuzaki) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
  • Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
  • 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.
  • Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
  • 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

  • Installation: Does installation proceed as outlined in the documentation?
  • Functionality: Have the functional claims of the software been confirmed?
  • 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

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

  • Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
  • 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?
  • State of the field: Do the authors describe how this software compares to other commonly-used packages?
  • Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
  • 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?

@kokitsuyuzaki
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@editorialbot generate pdf

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

@kokitsuyuzaki
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@ritika-giri Thank you for checking the install process. I replied your comment.
rikenbit/iTensor#3 (comment)

@ritika-giri
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@kokitsuyuzaki the install works now, thanks for fixing it!

@devarops
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devarops commented Jun 12, 2023

@osorensen:

Thank you for providing me with the opportunity to review the submission. After careful evaluation, I have found that while there are tests in place, they currently only cover approximately 35.8% of the code. In my opinion, this level of coverage is insufficient to adequately verify the functionality of the software.

In order to address this issue, I would like to suggest some minor revisions to elevate the test coverage. I propose aiming for a minimum coverage of 50% in each file, or preferably reaching a target of 90% coverage across the entire repository. By increasing the test coverage, we can significantly improve the reliability and robustness of the software, ensuring that potential issues are caught early and reducing the risk of regressions.

Please let me know if you have any further questions.

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Thanks a lot for your review @devarops. Your concern about test coverage seems very reasonable. Please let us know when this issue has been addressed, @kokitsuyuzaki.

@osorensen
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@devarops, is this issue addressed in a satisfactory way? If so, could you please update your checklist? Otherwise, please elaborate what the authors need to do further. Thank you.

@devarops
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@osorensen:
Yes, the authors have adequately resolved the issue. I recommend to accept this submission.

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@editorialbot generate pdf

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@editorialbot check references

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

OK DOIs

- None

MISSING DOIs

- 10.7551/mitpress/7011.003.0009 may be a valid DOI for title: An information-maximization approach to blind separation and blind deconvolution
- 10.1162/089976699300016719 may be a valid DOI for title: Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources
- 10.1109/72.761722 may be a valid DOI for title: Fast and robust fixed-point algorithms for independent component analysis
- 10.1049/ip-f-2.1993.0054 may be a valid DOI for title: Blind beamforming for non-gaussian signals
- 10.1007/978-3-642-15995-4_21 may be a valid DOI for title: Auxiliary-Function-Based Independent Component Analysis for Super-Gaussian Sources
- 10.1186/1471-2105-13-24 may be a valid DOI for title: Independent Principal Component Analysis for biologically meaningful dimension reduction of large biological data sets
- 10.1109/31.76486 may be a valid DOI for title: Indeterminacy and identifiability of blind identification
- 10.1109/icassp.1989.266878 may be a valid DOI for title: Source separation using higher order moments
- 10.1109/ijcnn.1999.831077 may be a valid DOI for title: MICA: Multimodal independent component analysis
- 10.1016/j.neuroimage.2008.10.057 may be a valid DOI for title: A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data
- 10.1016/j.sigpro.2022.108457 may be a valid DOI for title: CorrIndex: a permutation invariant performance index
- 10.1109/memb.2006.1607672 may be a valid DOI for title: Unmixing fMRI with Independent Component Analysis
- 10.1038/nbt.2859 may be a valid DOI for title: The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
- 10.3389/fnins.2013.00267 may be a valid DOI for title: MEG and EEG data analysis with MNE-Python
- 10.1371/journal.pone.0270556 may be a valid DOI for title: Comparing the reliability of different ICA algorithms for fMRI analysis
- 10.1109/spmb.2016.7846858 may be a valid DOI for title: Applying fully tensorial ICA to fMRI data

INVALID DOIs

- None

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

@osorensen
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@kokitsuyuzaki, both reviewers have now completed their checklist. I will now read through the paper, and let you know if there are any suggested changes from my side.

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

@osorensen
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Thanks @kokitsuyuzaki.

  • Could you please change the title of the Zenodo archive from "rikenbit/iTensor: iTensor: An R package for independent component analysis-based matrix/tensor decomposition" to "iTensor: An R package for independent component analysis-based matrix/tensor decomposition", so it exactly matches the paper?

  • Also, it is not necessary to include the name of me or any reviewers in the author list in the Zenodo archive. Could you please remove them? If you want to thank a review, please add an acknowledgement at the end of the paper instead.

Once done, please report back to me in this thread.

@kokitsuyuzaki
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Ok, I modified the title.
Sorry, the reviewers names seem to be automatically assigned in Zenodo.
I removed them now.
https://zenodo.org/record/8080600

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@editorialbot set 10.5281/zenodo.8080600 as archive

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Done! archive is now 10.5281/zenodo.8080600

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@editorialbot generate pdf

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

OK DOIs

- 10.7551/mitpress/7011.003.0009 is OK
- 10.1162/089976699300016719 is OK
- 10.1109/72.761722 is OK
- 10.1049/ip-f-2.1993.0054 is OK
- 10.1007/978-3-642-15995-4_21 is OK
- 10.1186/1471-2105-13-24 is OK
- 10.1109/31.76486 is OK
- 10.1109/icassp.1989.266878 is OK
- 10.1109/ijcnn.1999.831077 is OK
- 10.1016/j.neuroimage.2008.10.057 is OK
- 10.1016/j.sigpro.2022.108457 is OK
- 10.1109/memb.2006.1607672 is OK
- 10.1038/nbt.2859 is OK
- 10.3389/fnins.2013.00267 is OK
- 10.1371/journal.pone.0270556 is OK
- 10.1109/spmb.2016.7846858 is OK

MISSING DOIs

- None

INVALID DOIs

- None

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

@osorensen
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@kokitsuyuzaki, I notice another small thing that needs to be fixed before I can recommend acceptance. See PR in source repo.

@osorensen
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@kokitsuyuzaki, I notice another small thing that needs to be fixed before I can recommend acceptance. See PR in source repo.

I changed my mind. See comment in PR.

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@editorialbot recommend-accept

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Attempting dry run of processing paper acceptance...

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

OK DOIs

- 10.7551/mitpress/7011.003.0009 is OK
- 10.1162/089976699300016719 is OK
- 10.1109/72.761722 is OK
- 10.1049/ip-f-2.1993.0054 is OK
- 10.1007/978-3-642-15995-4_21 is OK
- 10.1186/1471-2105-13-24 is OK
- 10.1109/31.76486 is OK
- 10.1109/icassp.1989.266878 is OK
- 10.1109/ijcnn.1999.831077 is OK
- 10.1016/j.neuroimage.2008.10.057 is OK
- 10.1016/j.sigpro.2022.108457 is OK
- 10.1109/memb.2006.1607672 is OK
- 10.1038/nbt.2859 is OK
- 10.3389/fnins.2013.00267 is OK
- 10.1371/journal.pone.0270556 is OK
- 10.1109/spmb.2016.7846858 is OK

MISSING DOIs

- None

INVALID DOIs

- None

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👋 @openjournals/dsais-eics, this paper is ready to be accepted and published.

Check final proof 👉📄 Download article

If the paper PDF and the deposit XML files look good in openjournals/joss-papers#4347, then you can now move forward with accepting the submission by compiling again with the command @editorialbot accept

@editorialbot editorialbot added the recommend-accept Papers recommended for acceptance in JOSS. label Jun 26, 2023
@kokitsuyuzaki
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@osorensen Is there anything else I have to do?

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osorensen commented Jul 7, 2023

@kokitsuyuzaki, no, we're waiting for the editor-in-chief @openjournals/dsais-eics to read through and make the final decision.

@kyleniemeyer kyleniemeyer removed the waitlisted Submissions in the JOSS backlog due to reduced service mode. label Jul 7, 2023
@gkthiruvathukal
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@kokitsuyuzaki Working on this today (now). Thank you for your patience!

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@editorialbot accept

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Doing it live! Attempting automated processing of paper acceptance...

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Ensure proper citation by uploading a plain text CITATION.cff file to the default branch of your repository.

If using GitHub, a Cite this repository menu will appear in the About section, containing both APA and BibTeX formats. When exported to Zotero using a browser plugin, Zotero will automatically create an entry using the information contained in the .cff file.

You can copy the contents for your CITATION.cff file here:

CITATION.cff

cff-version: "1.2.0"
authors:
- family-names: Tsuyuzaki
  given-names: Koki
  orcid: "https://orcid.org/0000-0003-3797-2148"
doi: 10.5281/zenodo.8080600
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Tsuyuzaki
    given-names: Koki
    orcid: "https://orcid.org/0000-0003-3797-2148"
  date-published: 2023-07-07
  doi: 10.21105/joss.05496
  issn: 2475-9066
  issue: 87
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 5496
  title: "iTensor: An R package for independent component analysis-based
    matrix/tensor decomposition"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.05496"
  volume: 8
title: "iTensor: An R package for independent component analysis-based
  matrix/tensor decomposition"

If the repository is not hosted on GitHub, a .cff file can still be uploaded to set your preferred citation. Users will be able to manually copy and paste the citation.

Find more information on .cff files here and here.

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🐘🐘🐘 👉 Toot for this paper 👈 🐘🐘🐘

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🚨🚨🚨 THIS IS NOT A DRILL, YOU HAVE JUST ACCEPTED A PAPER INTO JOSS! 🚨🚨🚨

Here's what you must now do:

  1. Check final PDF and Crossref metadata that was deposited 👉 Creating pull request for 10.21105.joss.05496 joss-papers#4389
  2. Wait a couple of minutes, then verify that the paper DOI resolves https://doi.org/10.21105/joss.05496
  3. If everything looks good, then close this review issue.
  4. Party like you just published a paper! 🎉🌈🦄💃👻🤘

Any issues? Notify your editorial technical team...

@editorialbot editorialbot added accepted published Papers published in JOSS labels Jul 7, 2023
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🎉🎉🎉 Congratulations on your paper acceptance! 🎉🎉🎉

If you would like to include a link to your paper from your README use the following code snippets:

Markdown:
[![DOI](https://joss.theoj.org/papers/10.21105/joss.05496/status.svg)](https://doi.org/10.21105/joss.05496)

HTML:
<a style="border-width:0" href="https://doi.org/10.21105/joss.05496">
  <img src="https://joss.theoj.org/papers/10.21105/joss.05496/status.svg" alt="DOI badge" >
</a>

reStructuredText:
.. image:: https://joss.theoj.org/papers/10.21105/joss.05496/status.svg
   :target: https://doi.org/10.21105/joss.05496

This is how it will look in your documentation:

DOI

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