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[REVIEW]: ISL: A Julia package for training Implicit Generative Models via an Invariant Statistical Loss #7272

Open editorialbot opened 2 months ago

editorialbot commented 2 months ago

Submitting author: !--author-handle-->@https://github.com/josemanuel22<!--end-author-handle-- (José Manuel de Frutos) Repository: https://github.com/josemanuel22/ISL Branch with paper.md (empty if default branch): Version: v0.1.0 Editor: !--editor-->@bmcfee<!--end-editor-- Reviewers: @ziyiyin97, @odunbar Archive: Pending

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@ziyiyin97 & @odunbar, 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:

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The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @bmcfee 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 @ziyiyin97

📝 Checklist for @odunbar

editorialbot commented 2 months ago

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editorialbot commented 2 months ago

Software report:

github.com/AlDanial/cloc v 1.90  T=0.08 s (492.9 files/s, 314372.0 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
CSV                              1              0              0          17421
Julia                           18            752           1095           3027
Markdown                         6            172              0            479
TeX                              1             53              0            387
YAML                             6              8              9            123
TOML                             4              4              0             47
SVG                              1              0              1             20
-------------------------------------------------------------------------------
SUM:                            37            989           1105          21504
-------------------------------------------------------------------------------

Commit count by author:

   332  josemanuel22
    33  José Manuel de Frutos
    21  José Manuel Frutos
editorialbot commented 2 months ago

Paper file info:

📄 Wordcount for paper.md is 1031

✅ The paper includes a Statement of need section

editorialbot commented 2 months ago

License info:

✅ License found: MIT License (Valid open source OSI approved license)

editorialbot commented 2 months ago 
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

✅ OK DOIs

- 10.1080/00031305.2017.1380080 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: On the performance of particle filters with adapti...
- No DOI given, and none found for title: Enhancing the Locality and Breaking the Memory Bot...
- No DOI given, and none found for title: GAN connoisseur: Can GANs learn simple 1D parametr...
- No DOI given, and none found for title: Generative adversarial nets
- No DOI given, and none found for title: Generalization and equilibrium in generative adver...
- No DOI given, and none found for title: Wasserstein generative adversarial networks
- No DOI given, and none found for title: MMD GAN: Towards deeper understanding of moment ma...
- No DOI given, and none found for title: Do GANs actually learn the distribution? an empiri...
- No DOI given, and none found for title: Probability and Measure
- No DOI given, and none found for title: f-GAN: Training generative neural samplers using v...
- No DOI given, and none found for title: Adversarial variational bayes: Unifying variationa...
- No DOI given, and none found for title: Generative moment matching networks
- No DOI given, and none found for title: A kernel two-sample test
- No DOI given, and none found for title: Function-space inference with sparse implicit proc...
- No DOI given, and none found for title: Probabilistic time series forecasting with implici...
- No DOI given, and none found for title: Multivariate Probabilistic Time Series Forecasting...
- No DOI given, and none found for title: Deep State Space Models for Time Series Forecastin...
- No DOI given, and none found for title: Temporal Regularized Matrix Factorization for High...
- No DOI given, and none found for title: Time Series Analysis: Forecasting and Control, 5th...
- No DOI given, and none found for title: Autoregressive Denoising Diffusion Models for Mult...
- No DOI given, and none found for title: Do GANs learn the distribution? some theory and em...
- No DOI given, and none found for title: Deep autoregressive models with spectral attention
- No DOI given, and none found for title: Training generative neural networks via maximum me...
- No DOI given, and none found for title: Nonparametric density estimation & convergence rat...
- No DOI given, and none found for title: ElectricityLoadDiagrams20112014
- No DOI given, and none found for title: Enhancing the locality and breaking the memory bot...
- No DOI given, and none found for title: Independent random sampling methods
- No DOI given, and none found for title: Adam: A method for stochastic optimization
- No DOI given, and none found for title: Improved techniques for training GANs
- No DOI given, and none found for title: Spectral normalization for generative adversarial ...
- No DOI given, and none found for title: Learning in implicit generative models
- No DOI given, and none found for title: 30 Years of European Wind Generation
- No DOI given, and none found for title: Gluonts: Probabilistic and neural time series mode...
- No DOI given, and none found for title: Autoformer: Decomposition transformers with auto-c...
- No DOI given, and none found for title: On the measure of Voronoi cells
- No DOI given, and none found for title: Understanding and contextualising diffusion models
- No DOI given, and none found for title: Training Implicit Generative Models via an Invaria...

❌ MISSING DOIs

- 10.1109/tsp.2016.2637324 may be a valid DOI for title: Adapting the number of particles in sequential Mon...
- 10.1109/icassp.2016.7472504 may be a valid DOI for title: Online adaptation of the number of particles of SM...
- 10.1109/iccv.2019.00456 may be a valid DOI for title: Learning implicit generative models by matching pe...
- 10.1214/aoms/1177729394 may be a valid DOI for title: Remarks on a multivariate transformation
- 10.1016/j.ijforecast.2019.07.001 may be a valid DOI for title: DeepAR: Probabilistic forecasting with autoregress...
- 10.1109/tsp.2010.2053707 may be a valid DOI for title: Assessment of nonlinear dynamic models by Kolmogor...
- 10.1609/aaai.v35i12.17325 may be a valid DOI for title: Informer: Beyond efficient transformer for long se...
- 10.1609/aaai.v37i9.26317 may be a valid DOI for title: Are transformers effective for time series forecas...
- 10.1109/cvpr.2018.00367 may be a valid DOI for title: Generative modeling using the sliced wasserstein d...

❌ INVALID DOIs

- None
editorialbot commented 2 months ago

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

ziyiyin97 commented 2 months ago

Review checklist for @ziyiyin97

Conflict of interest

Code of Conduct

General checks

Functionality

Documentation

Software paper

odunbar commented 2 months ago

Review checklist for @odunbar

Conflict of interest

Code of Conduct

General checks

Functionality

Documentation

Software paper

odunbar commented 1 month ago

Hi folks, just working on the review here, I had a question about plagiarism,

Despite this being the authors own work, I assume this counts as plagiarism and should be changed sufficiently in wording for the JOSS publication? Or is this "OK" here?

Edit: One other curious note on plagiarism

I have left a review comment at https://github.com/josemanuel22/ISL/issues/8

bmcfee commented 1 month ago

Thanks @odunbar for raising this. I think the relevant part of the submission guidelines is here:

Co-publication of science, methods, and software

Sometimes authors prepare a JOSS publication alongside a contribution describing a science application, details of algorithm development, and/or methods assessment. In this circumstance, JOSS considers submissions for which the implementation of the software itself reflects a substantial scientific effort. This may be represented by the design of the software, the implementation of the algorithms, creation of tutorials, or any other aspect of the software. We ask that authors indicate whether related publications (published, in review, or nearing submission) exist as part of submitting to JOSS.

In this case, the related paper is cited in the JOSS submission, but there was not a separate explicit mention of the work in the submission thread.

I've bumped this up to @openjournals/joss-eics for comment, and will get back to this shortly.

bmcfee commented 1 month ago

@josemanuel22 After discussing with EiCs, we agree that the verbatim text in the summary and statement of need would constitute self-plagiarism and should be rewritten. Can you take care of this, and respond back in this thread?

bmcfee commented 1 day ago

@josemanuel22 checking back on this - has there been any update here?