-
Notifications
You must be signed in to change notification settings - Fork 19
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #5710 from openjournals/joss.06794
Merging automatically
- Loading branch information
Showing
3 changed files
with
817 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,248 @@ | ||
<?xml version="1.0" encoding="UTF-8"?> | ||
<doi_batch xmlns="http://www.crossref.org/schema/5.3.1" | ||
xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" | ||
xmlns:rel="http://www.crossref.org/relations.xsd" | ||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" | ||
version="5.3.1" | ||
xsi:schemaLocation="http://www.crossref.org/schema/5.3.1 http://www.crossref.org/schemas/crossref5.3.1.xsd"> | ||
<head> | ||
<doi_batch_id>20240730210706-6f20f03410e17cc3fb35e104b63e493419ea235c</doi_batch_id> | ||
<timestamp>20240730210706</timestamp> | ||
<depositor> | ||
<depositor_name>JOSS Admin</depositor_name> | ||
<email_address>admin@theoj.org</email_address> | ||
</depositor> | ||
<registrant>The Open Journal</registrant> | ||
</head> | ||
<body> | ||
<journal> | ||
<journal_metadata> | ||
<full_title>Journal of Open Source Software</full_title> | ||
<abbrev_title>JOSS</abbrev_title> | ||
<issn media_type="electronic">2475-9066</issn> | ||
<doi_data> | ||
<doi>10.21105/joss</doi> | ||
<resource>https://joss.theoj.org</resource> | ||
</doi_data> | ||
</journal_metadata> | ||
<journal_issue> | ||
<publication_date media_type="online"> | ||
<month>07</month> | ||
<year>2024</year> | ||
</publication_date> | ||
<journal_volume> | ||
<volume>9</volume> | ||
</journal_volume> | ||
<issue>99</issue> | ||
</journal_issue> | ||
<journal_article publication_type="full_text"> | ||
<titles> | ||
<title>AutoEncoderToolkit.jl: A Julia package for training | ||
(Variational) Autoencoders</title> | ||
</titles> | ||
<contributors> | ||
<person_name sequence="first" contributor_role="author"> | ||
<given_name>Manuel</given_name> | ||
<surname>Razo-Mejia</surname> | ||
<ORCID>https://orcid.org/0000-0002-9510-0527</ORCID> | ||
</person_name> | ||
</contributors> | ||
<publication_date> | ||
<month>07</month> | ||
<day>30</day> | ||
<year>2024</year> | ||
</publication_date> | ||
<pages> | ||
<first_page>6794</first_page> | ||
</pages> | ||
<publisher_item> | ||
<identifier id_type="doi">10.21105/joss.06794</identifier> | ||
</publisher_item> | ||
<ai:program name="AccessIndicators"> | ||
<ai:license_ref applies_to="vor">http://creativecommons.org/licenses/by/4.0/</ai:license_ref> | ||
<ai:license_ref applies_to="am">http://creativecommons.org/licenses/by/4.0/</ai:license_ref> | ||
<ai:license_ref applies_to="tdm">http://creativecommons.org/licenses/by/4.0/</ai:license_ref> | ||
</ai:program> | ||
<rel:program> | ||
<rel:related_item> | ||
<rel:description>Software archive</rel:description> | ||
<rel:inter_work_relation relationship-type="references" identifier-type="doi">10.5281/zenodo.12802504</rel:inter_work_relation> | ||
</rel:related_item> | ||
<rel:related_item> | ||
<rel:description>GitHub review issue</rel:description> | ||
<rel:inter_work_relation relationship-type="hasReview" identifier-type="uri">https://github.com/openjournals/joss-reviews/issues/6794</rel:inter_work_relation> | ||
</rel:related_item> | ||
</rel:program> | ||
<doi_data> | ||
<doi>10.21105/joss.06794</doi> | ||
<resource>https://joss.theoj.org/papers/10.21105/joss.06794</resource> | ||
<collection property="text-mining"> | ||
<item> | ||
<resource mime_type="application/pdf">https://joss.theoj.org/papers/10.21105/joss.06794.pdf</resource> | ||
</item> | ||
</collection> | ||
</doi_data> | ||
<citation_list> | ||
<citation key="arvanitidis2021"> | ||
<article_title>Latent Space Oddity: On the Curvature of Deep | ||
Generative Models</article_title> | ||
<author>Arvanitidis</author> | ||
<doi>10.48550/arXiv.1710.11379</doi> | ||
<cYear>2021</cYear> | ||
<unstructured_citation>Arvanitidis, G., Hansen, L. K., & | ||
Hauberg, S. (2021, December 13). Latent Space Oddity: On the Curvature | ||
of Deep Generative Models. | ||
https://doi.org/10.48550/arXiv.1710.11379</unstructured_citation> | ||
</citation> | ||
<citation key="caterini2018"> | ||
<article_title>Hamiltonian Variational | ||
Auto-Encoder</article_title> | ||
<author>Caterini</author> | ||
<doi>10.48550/arXiv.1805.11328</doi> | ||
<cYear>2018</cYear> | ||
<unstructured_citation>Caterini, A. L., Doucet, A., & | ||
Sejdinovic, D. (2018). Hamiltonian Variational Auto-Encoder. 11. | ||
https://doi.org/10.48550/arXiv.1805.11328</unstructured_citation> | ||
</citation> | ||
<citation key="chadebec2020"> | ||
<article_title>Geometry-Aware Hamiltonian Variational | ||
Auto-Encoder</article_title> | ||
<author>Chadebec</author> | ||
<doi>10.48550/arXiv.2010.11518</doi> | ||
<cYear>2020</cYear> | ||
<unstructured_citation>Chadebec, C., Mantoux, C., & | ||
Allassonnière, S. (2020, October 22). Geometry-Aware Hamiltonian | ||
Variational Auto-Encoder. | ||
https://doi.org/10.48550/arXiv.2010.11518</unstructured_citation> | ||
</citation> | ||
<citation key="chadebec2022"> | ||
<article_title>A Geometric Perspective on Variational | ||
Autoencoders</article_title> | ||
<author>Chadebec</author> | ||
<doi>10.48550/arXiv.2209.07370</doi> | ||
<cYear>2022</cYear> | ||
<unstructured_citation>Chadebec, C., & Allassonnière, S. | ||
(2022, November 3). A Geometric Perspective on Variational Autoencoders. | ||
https://doi.org/10.48550/arXiv.2209.07370</unstructured_citation> | ||
</citation> | ||
<citation key="champion2019"> | ||
<article_title>Data-driven discovery of coordinates and | ||
governing equations</article_title> | ||
<author>Champion</author> | ||
<journal_title>Proceedings of the National Academy of | ||
Sciences</journal_title> | ||
<issue>45</issue> | ||
<volume>116</volume> | ||
<doi>10.1073/pnas.1906995116</doi> | ||
<issn>0027-8424</issn> | ||
<cYear>2019</cYear> | ||
<unstructured_citation>Champion, K., Lusch, B., Kutz, J. N., | ||
& Brunton, S. L. (2019). Data-driven discovery of coordinates and | ||
governing equations. Proceedings of the National Academy of Sciences, | ||
116(45), 22445–22451. | ||
https://doi.org/10.1073/pnas.1906995116</unstructured_citation> | ||
</citation> | ||
<citation key="chen2018a"> | ||
<article_title>Metrics for Deep Generative | ||
Models</article_title> | ||
<author>Chen</author> | ||
<journal_title>Proceedings of the Twenty-First International | ||
Conference on Artificial Intelligence and Statistics</journal_title> | ||
<issn>2640-3498</issn> | ||
<cYear>2018</cYear> | ||
<unstructured_citation>Chen, N., Klushyn, A., Kurle, R., | ||
Jiang, X., Bayer, J., & Smagt, P. (2018). Metrics for Deep | ||
Generative Models. Proceedings of the Twenty-First International | ||
Conference on Artificial Intelligence and Statistics, 1540–1550. | ||
https://proceedings.mlr.press/v84/chen18e.html</unstructured_citation> | ||
</citation> | ||
<citation key="higgins2017a"> | ||
<article_title>Β-VAE: Learning Basic Visual Concepts with a | ||
Constrained Variational Framework</article_title> | ||
<author>Higgins</author> | ||
<cYear>2017</cYear> | ||
<unstructured_citation>Higgins, I., Matthey, L., Pal, A., | ||
Burgess, C., Glorot, X., Botvinick, M., Mohamed, S., & Lerchner, A. | ||
(2017). Β-VAE: Learning Basic Visual Concepts with a Constrained | ||
Variational Framework. | ||
https://openreview.net/forum?id=Sy2fzU9gl</unstructured_citation> | ||
</citation> | ||
<citation key="innes2018"> | ||
<article_title>Flux: Elegant machine learning with | ||
Julia</article_title> | ||
<author>Innes</author> | ||
<journal_title>Journal of Open Source | ||
Software</journal_title> | ||
<issue>25</issue> | ||
<volume>3</volume> | ||
<doi>10.21105/joss.00602</doi> | ||
<issn>2475-9066</issn> | ||
<cYear>2018</cYear> | ||
<unstructured_citation>Innes, M. (2018). Flux: Elegant | ||
machine learning with Julia. Journal of Open Source Software, 3(25), | ||
602. https://doi.org/10.21105/joss.00602</unstructured_citation> | ||
</citation> | ||
<citation key="kingma2014"> | ||
<article_title>Auto-Encoding Variational | ||
Bayes</article_title> | ||
<author>Kingma</author> | ||
<doi>10.48550/arXiv.1312.6114</doi> | ||
<cYear>2014</cYear> | ||
<unstructured_citation>Kingma, D. P., & Welling, M. | ||
(2014, May 1). Auto-Encoding Variational Bayes. | ||
https://doi.org/10.48550/arXiv.1312.6114</unstructured_citation> | ||
</citation> | ||
<citation key="lian2022"> | ||
<article_title>Deep learning-enabled design of synthetic | ||
orthologs of a signaling protein</article_title> | ||
<author>Lian</author> | ||
<doi>10.1101/2022.12.21.521443</doi> | ||
<cYear>2022</cYear> | ||
<unstructured_citation>Lian, X., Praljak, N., Subramanian, | ||
S. K., Wasinger, S., Ranganathan, R., & Ferguson, A. L. (2022). Deep | ||
learning-enabled design of synthetic orthologs of a signaling protein | ||
[Preprint]. Molecular Biology. | ||
https://doi.org/10.1101/2022.12.21.521443</unstructured_citation> | ||
</citation> | ||
<citation key="lopez2018"> | ||
<article_title>Deep generative modeling for single-cell | ||
transcriptomics</article_title> | ||
<author>Lopez</author> | ||
<journal_title>Nature Methods</journal_title> | ||
<issue>12</issue> | ||
<volume>15</volume> | ||
<doi>10.1038/s41592-018-0229-2</doi> | ||
<issn>1548-7105</issn> | ||
<cYear>2018</cYear> | ||
<unstructured_citation>Lopez, R., Regier, J., Cole, M. B., | ||
Jordan, M. I., & Yosef, N. (2018). Deep generative modeling for | ||
single-cell transcriptomics. Nature Methods, 15(12), 1053–1058. | ||
https://doi.org/10.1038/s41592-018-0229-2</unstructured_citation> | ||
</citation> | ||
<citation key="rezaabad2020"> | ||
<article_title>Learning Representations by Maximizing Mutual | ||
Information in Variational Autoencoders</article_title> | ||
<author>Rezaabad</author> | ||
<doi>10.48550/arXiv.1912.13361</doi> | ||
<cYear>2020</cYear> | ||
<unstructured_citation>Rezaabad, A. L., & Vishwanath, S. | ||
(2020, January 7). Learning Representations by Maximizing Mutual | ||
Information in Variational Autoencoders. | ||
https://doi.org/10.48550/arXiv.1912.13361</unstructured_citation> | ||
</citation> | ||
<citation key="zhao2018"> | ||
<article_title>InfoVAE: Information Maximizing Variational | ||
Autoencoders</article_title> | ||
<author>Zhao</author> | ||
<doi>10.48550/arXiv.1706.02262</doi> | ||
<cYear>2018</cYear> | ||
<unstructured_citation>Zhao, S., Song, J., & Ermon, S. | ||
(2018, May 30). InfoVAE: Information Maximizing Variational | ||
Autoencoders. | ||
https://doi.org/10.48550/arXiv.1706.02262</unstructured_citation> | ||
</citation> | ||
</citation_list> | ||
</journal_article> | ||
</journal> | ||
</body> | ||
</doi_batch> |
Binary file not shown.
Oops, something went wrong.