Skip to content

Commit

Permalink
Merge pull request #5777 from openjournals/joss.06880
Browse files Browse the repository at this point in the history
Merging automatically
  • Loading branch information
editorialbot authored Aug 16, 2024
2 parents 4a70bea + 2a9a8c1 commit d9ec91e
Show file tree
Hide file tree
Showing 3 changed files with 920 additions and 0 deletions.
215 changes: 215 additions & 0 deletions joss.06880/10.21105.joss.06880.crossref.xml
Original file line number Diff line number Diff line change
@@ -0,0 +1,215 @@
<?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>20240816180609-c1ee3674cbf230ecb9afad2524f198a14c3254bf</doi_batch_id>
<timestamp>20240816180609</timestamp>
<depositor>
<depositor_name>JOSS Admin</depositor_name>
<email_address>[email protected]</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>08</month>
<year>2024</year>
</publication_date>
<journal_volume>
<volume>9</volume>
</journal_volume>
<issue>100</issue>
</journal_issue>
<journal_article publication_type="full_text">
<titles>
<title>ChainoPy: A Python Library for Discrete Time Markov
Chain Based Stochastic Analysis</title>
</titles>
<contributors>
<person_name sequence="first" contributor_role="author">
<given_name>Aadya A.</given_name>
<surname>Chinubhai</surname>
</person_name>
</contributors>
<publication_date>
<month>08</month>
<day>16</day>
<year>2024</year>
</publication_date>
<pages>
<first_page>6880</first_page>
</pages>
<publisher_item>
<identifier id_type="doi">10.21105/joss.06880</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.13305155</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/6880</rel:inter_work_relation>
</rel:related_item>
</rel:program>
<doi_data>
<doi>10.21105/joss.06880</doi>
<resource>https://joss.theoj.org/papers/10.21105/joss.06880</resource>
<collection property="text-mining">
<item>
<resource mime_type="application/pdf">https://joss.theoj.org/papers/10.21105/joss.06880.pdf</resource>
</item>
</collection>
</doi_data>
<citation_list>
<citation key="awiszus2018markov">
<article_title>Markov chain neural networks</article_title>
<author>Awiszus</author>
<journal_title>Proceedings of the IEEE conference on
computer vision and pattern recognition workshops</journal_title>
<doi>10.1109/CVPRW.2018.00293</doi>
<cYear>2018</cYear>
<unstructured_citation>Awiszus, M., &amp; Rosenhahn, B.
(2018). Markov chain neural networks. Proceedings of the IEEE Conference
on Computer Vision and Pattern Recognition Workshops, 2180–2187.
https://doi.org/10.1109/CVPRW.2018.00293</unstructured_citation>
</citation>
<citation key="pydtmc">
<article_title>PyDTMC</article_title>
<author>Belluzzo</author>
<cYear>2024</cYear>
<unstructured_citation>Belluzzo, T. (2024). PyDTMC.
https://github.com/TommasoBelluzzo/PyDTMC.
https://github.com/TommasoBelluzzo/PyDTMC</unstructured_citation>
</citation>
<citation key="simple-markov">
<article_title>Simple-markov</article_title>
<author>Charisopoulos</author>
<cYear>2016</cYear>
<unstructured_citation>Charisopoulos, V., &amp;
Andrikopoulos, K. (2016). Simple-markov.
https://github.com/Mandragorian/simple-markov.
https://github.com/Mandragorian/simple-markov</unstructured_citation>
</citation>
<citation key="mchmm">
<article_title>Mchmm</article_title>
<author>Terpilovskii</author>
<cYear>2021</cYear>
<unstructured_citation>Terpilovskii, M. (2021). Mchmm.
https://github.com/maximtrp/mchmm.
https://github.com/maximtrp/mchmm</unstructured_citation>
</citation>
<citation key="behnel2010cython">
<article_title>Cython: The best of both
worlds</article_title>
<author>Behnel</author>
<journal_title>Computing in Science &amp;
Engineering</journal_title>
<issue>2</issue>
<volume>13</volume>
<doi>10.1109/MCSE.2010.118</doi>
<cYear>2010</cYear>
<unstructured_citation>Behnel, S., Bradshaw, R., Citro, C.,
Dalcin, L., Seljebotn, D. S., &amp; Smith, K. (2010). Cython: The best
of both worlds. Computing in Science &amp; Engineering, 13(2), 31–39.
https://doi.org/10.1109/MCSE.2010.118</unstructured_citation>
</citation>
<citation key="harris2020array">
<article_title>Array programming with NumPy</article_title>
<author>Harris</author>
<journal_title>Nature</journal_title>
<issue>7825</issue>
<volume>585</volume>
<doi>10.1038/s41586-020-2649-2</doi>
<cYear>2020</cYear>
<unstructured_citation>Harris, C. R., Millman, K. J., Van
Der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E.,
Taylor, J., Berg, S., Smith, N. J., &amp; others. (2020). Array
programming with NumPy. Nature, 585(7825), 357–362.
https://doi.org/10.1038/s41586-020-2649-2</unstructured_citation>
</citation>
<citation key="virtanen2020scipy">
<article_title>SciPy 1.0: Fundamental algorithms for
scientific computing in python</article_title>
<author>Virtanen</author>
<journal_title>Nature methods</journal_title>
<issue>3</issue>
<volume>17</volume>
<doi>10.1038/s41592-019-0686-2</doi>
<cYear>2020</cYear>
<unstructured_citation>Virtanen, P., Gommers, R., Oliphant,
T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson,
P., Weckesser, W., Bright, J., &amp; others. (2020). SciPy 1.0:
Fundamental algorithms for scientific computing in python. Nature
Methods, 17(3), 261–272.
https://doi.org/10.1038/s41592-019-0686-2</unstructured_citation>
</citation>
<citation key="ansel2024pytorch">
<article_title>PyTorch 2: Faster machine learning through
dynamic python bytecode transformation and graph
compilation</article_title>
<author>Ansel</author>
<journal_title>Proceedings of the 29th ACM international
conference on architectural support for programming languages and
operating systems, volume 2</journal_title>
<doi>10.1145/3620665.3640366</doi>
<cYear>2024</cYear>
<unstructured_citation>Ansel, J., Yang, E., He, H.,
Gimelshein, N., Jain, A., Voznesensky, M., Bao, B., Bell, P., Berard,
D., Burovski, E., &amp; others. (2024). PyTorch 2: Faster machine
learning through dynamic python bytecode transformation and graph
compilation. Proceedings of the 29th ACM International Conference on
Architectural Support for Programming Languages and Operating Systems,
Volume 2, 929–947.
https://doi.org/10.1145/3620665.3640366</unstructured_citation>
</citation>
<citation key="rosenthal1995convergence">
<article_title>Convergence rates for markov
chains</article_title>
<author>Rosenthal</author>
<journal_title>SIAM Review</journal_title>
<issue>3</issue>
<volume>37</volume>
<doi>10.1137/1037083</doi>
<cYear>1995</cYear>
<unstructured_citation>Rosenthal, J. S. (1995). Convergence
rates for markov chains. SIAM Review, 37(3), 387–405.
https://doi.org/10.1137/1037083</unstructured_citation>
</citation>
<citation key="hamilton2010regime">
<article_title>Regime switching models</article_title>
<author>Hamilton</author>
<journal_title>Macroeconometrics and time series
analysis</journal_title>
<doi>10.1057/9780230280830_23</doi>
<cYear>2010</cYear>
<unstructured_citation>Hamilton, J. D. (2010). Regime
switching models. In Macroeconometrics and time series analysis (pp.
202–209). Springer.
https://doi.org/10.1057/9780230280830_23</unstructured_citation>
</citation>
</citation_list>
</journal_article>
</journal>
</body>
</doi_batch>
Binary file added joss.06880/10.21105.joss.06880.pdf
Binary file not shown.
Loading

0 comments on commit d9ec91e

Please sign in to comment.