Skip to content

Commit 36a168d

Browse files
editorialboteditorialbot
authored
Merge pull request #8065 from openjournals/joss.10130
Merging automatically
2 parents 8d56bf6 + c40d162 commit 36a168d

5 files changed

Lines changed: 664 additions & 0 deletions

File tree

‎joss.10130/10.21105.joss.10130.crossref.xml‎

Lines changed: 185 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,185 @@
1+
<?xml version="1.0" encoding="UTF-8"?>
2+
<doi_batch xmlns="http://www.crossref.org/schema/5.3.1"
3+
xmlns:ai="http://www.crossref.org/AccessIndicators.xsd"
4+
xmlns:rel="http://www.crossref.org/relations.xsd"
5+
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
6+
version="5.3.1"
7+
xsi:schemaLocation="http://www.crossref.org/schema/5.3.1 http://www.crossref.org/schemas/crossref5.3.1.xsd">
8+
<head>
9+
<doi_batch_id>20260428124934-b84561e6879f1b31021b8459f84b5789d184f572</doi_batch_id>
10+
<timestamp>20260428124934</timestamp>
11+
<depositor>
12+
<depositor_name>JOSS Admin</depositor_name>
13+
<email_address>[email protected]</email_address>
14+
</depositor>
15+
<registrant>The Open Journal</registrant>
16+
</head>
17+
<body>
18+
<journal>
19+
<journal_metadata>
20+
<full_title>Journal of Open Source Software</full_title>
21+
<abbrev_title>JOSS</abbrev_title>
22+
<issn media_type="electronic">2475-9066</issn>
23+
<doi_data>
24+
<doi>10.21105/joss</doi>
25+
<resource>https://joss.theoj.org</resource>
26+
</doi_data>
27+
</journal_metadata>
28+
<journal_issue>
29+
<publication_date media_type="online">
30+
<month>04</month>
31+
<year>2026</year>
32+
</publication_date>
33+
<journal_volume>
34+
<volume>11</volume>
35+
</journal_volume>
36+
<issue>120</issue>
37+
</journal_issue>
38+
<journal_article publication_type="full_text">
39+
<titles>
40+
<title>ImageMLResearch: A Python Toolkit for Reproducible Image-Based ML Experiments</title>
41+
</titles>
42+
<contributors>
43+
<person_name sequence="first" contributor_role="author">
44+
<given_name>Luis</given_name>
45+
<surname>Kraker</surname>
46+
<affiliations>
47+
<institution><institution_name>FH JOANNEUM University of Applied Sciences, Graz, Austria</institution_name><institution_id type="ror">https://ror.org/01x3znb20</institution_id></institution>
48+
</affiliations>
49+
<ORCID>https://orcid.org/0009-0009-8692-9227</ORCID>
50+
</person_name>
51+
<person_name sequence="additional"
52+
contributor_role="author">
53+
<given_name>Gudrun</given_name>
54+
<surname>Schappacher-Tilp</surname>
55+
<affiliations>
56+
<institution><institution_name>FH JOANNEUM University of Applied Sciences, Graz, Austria</institution_name><institution_id type="ror">https://ror.org/01x3znb20</institution_id></institution>
57+
</affiliations>
58+
<ORCID>https://orcid.org/0000-0001-9078-0044</ORCID>
59+
</person_name>
60+
</contributors>
61+
<publication_date>
62+
<month>04</month>
63+
<day>28</day>
64+
<year>2026</year>
65+
</publication_date>
66+
<pages>
67+
<first_page>10130</first_page>
68+
</pages>
69+
<publisher_item>
70+
<identifier id_type="doi">10.21105/joss.10130</identifier>
71+
</publisher_item>
72+
<ai:program name="AccessIndicators">
73+
<ai:license_ref applies_to="vor">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
74+
<ai:license_ref applies_to="am">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
75+
<ai:license_ref applies_to="tdm">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
76+
</ai:program>
77+
<rel:program>
78+
<rel:related_item>
79+
<rel:description>Software archive</rel:description>
80+
<rel:inter_work_relation relationship-type="references" identifier-type="doi">10.5281/zenodo.19738821</rel:inter_work_relation>
81+
</rel:related_item>
82+
<rel:related_item>
83+
<rel:description>GitHub review issue</rel:description>
84+
<rel:inter_work_relation relationship-type="hasReview" identifier-type="uri">https://github.com/openjournals/joss-reviews/issues/10130</rel:inter_work_relation>
85+
</rel:related_item>
86+
</rel:program>
87+
<doi_data>
88+
<doi>10.21105/joss.10130</doi>
89+
<resource>https://joss.theoj.org/papers/10.21105/joss.10130</resource>
90+
<collection property="text-mining">
91+
<item>
92+
<resource mime_type="application/pdf">https://joss.theoj.org/papers/10.21105/joss.10130.pdf</resource>
93+
</item>
94+
</collection>
95+
</doi_data>
96+
<citation_list>
97+
<citation key="abadi2016tensorflow">
98+
<article_title>TensorFlow: A system for large-scale machine learning</article_title>
99+
<author>Abadi</author>
100+
<journal_title>12th USENIX symposium on operating systems design and implementation (OSDI 16)</journal_title>
101+
<cYear>2016</cYear>
102+
<unstructured_citation>Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., Kudlur, M., Levenberg, J., Monga, R., Moore, S., Murray, D. G., Steiner, B., Tucker, P., Vasudevan, V., Warden, P., … Zheng, X. (2016). TensorFlow: A system for large-scale machine learning. 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16), 265–283. https://www.usenix.org/conference/osdi16/technical-sessions/presentation/abadi</unstructured_citation>
103+
</citation>
104+
<citation key="chollet2015keras">
105+
<article_title>Keras</article_title>
106+
<author>Chollet</author>
107+
<cYear>2015</cYear>
108+
<unstructured_citation>Chollet, F., &amp; others. (2015). Keras (Version 3.12.1). https://github.com/keras-team/keras</unstructured_citation>
109+
</citation>
110+
<citation key="akiba2019optuna">
111+
<article_title>Optuna: A next-generation hyperparameter optimization framework</article_title>
112+
<author>Akiba</author>
113+
<journal_title>Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery &amp; data mining</journal_title>
114+
<doi>10.1145/3292500.3330701</doi>
115+
<cYear>2019</cYear>
116+
<unstructured_citation>Akiba, T., Sano, S., Yanase, T., Ohta, T., &amp; Koyama, M. (2019). Optuna: A next-generation hyperparameter optimization framework. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining, 2623–2631. https://doi.org/10.1145/3292500.3330701</unstructured_citation>
117+
</citation>
118+
<citation key="gundersen2018reproducible">
119+
<article_title>On reproducible AI: Towards reproducible research, open science, and digital scholarship in AI publications</article_title>
120+
<author>Gundersen</author>
121+
<journal_title>AI Magazine</journal_title>
122+
<issue>3</issue>
123+
<volume>39</volume>
124+
<doi>10.1609/aimag.v39i3.2816</doi>
125+
<cYear>2018</cYear>
126+
<unstructured_citation>Gundersen, O. E., Gil, Y., &amp; Aha, D. W. (2018). On reproducible AI: Towards reproducible research, open science, and digital scholarship in AI publications. AI Magazine, 39(3), 56–68. https://doi.org/10.1609/aimag.v39i3.2816</unstructured_citation>
127+
</citation>
128+
<citation key="pineau2021improving">
129+
<article_title>Improving reproducibility in machine learning research (a report from the NeurIPS 2019 reproducibility program)</article_title>
130+
<author>Pineau</author>
131+
<journal_title>arXiv preprint arXiv:2003.12206</journal_title>
132+
<doi>10.48550/arXiv.2003.12206</doi>
133+
<cYear>2021</cYear>
134+
<unstructured_citation>Pineau, J., Vincent-Lamarre, P., Sinha, K., Larivière, V., Beygelzimer, A., d’Alché-Buc, F., Fox, E., &amp; Larochelle, H. (2021). Improving reproducibility in machine learning research (a report from the NeurIPS 2019 reproducibility program). arXiv Preprint arXiv:2003.12206. https://doi.org/10.48550/arXiv.2003.12206</unstructured_citation>
135+
</citation>
136+
<citation key="hutson2018reproducibility">
137+
<article_title>Artificial intelligence faces reproducibility crisis</article_title>
138+
<author>Hutson</author>
139+
<journal_title>Science</journal_title>
140+
<issue>6377</issue>
141+
<volume>359</volume>
142+
<doi>10.1126/science.359.6377.725</doi>
143+
<cYear>2018</cYear>
144+
<unstructured_citation>Hutson, M. (2018). Artificial intelligence faces reproducibility crisis. Science, 359(6377), 725–726. https://doi.org/10.1126/science.359.6377.725</unstructured_citation>
145+
</citation>
146+
<citation key="paszke2019pytorch">
147+
<article_title>PyTorch: An imperative style, high-performance deep learning library</article_title>
148+
<author>Paszke</author>
149+
<journal_title>Advances in neural information processing systems</journal_title>
150+
<volume>32</volume>
151+
<cYear>2019</cYear>
152+
<unstructured_citation>Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., &amp; others. (2019). PyTorch: An imperative style, high-performance deep learning library. Advances in Neural Information Processing Systems, 32. https://dl.acm.org/doi/10.5555/3454287.3455008</unstructured_citation>
153+
</citation>
154+
<citation key="zaharia2018mlflow">
155+
<article_title>Accelerating the machine learning lifecycle with MLflow</article_title>
156+
<author>Zaharia</author>
157+
<journal_title>IEEE Data Engineering Bulletin</journal_title>
158+
<issue>4</issue>
159+
<volume>41</volume>
160+
<cYear>2018</cYear>
161+
<unstructured_citation>Zaharia, M., Chen, A., Davidson, A., Ghodsi, A., Hong, S. A., Konwinski, A., Murching, S., Nykodym, T., Ogilvie, P., Parkhe, M., Xie, F., &amp; Zumar, C. (2018). Accelerating the machine learning lifecycle with MLflow. IEEE Data Engineering Bulletin, 41(4), 39–45. https://people.eecs.berkeley.edu/~matei/papers/2018/ieee_mlflow.pdf</unstructured_citation>
162+
</citation>
163+
<citation key="biewald2020wandb">
164+
<article_title>Weights &amp; biases</article_title>
165+
<author>Biewald</author>
166+
<cYear>2020</cYear>
167+
<unstructured_citation>Biewald, L. (2020). Weights &amp; biases. https://wandb.ai/site/experiment-tracking/</unstructured_citation>
168+
</citation>
169+
<citation key="ruff">
170+
<article_title>Ruff</article_title>
171+
<author>astral-sh</author>
172+
<cYear>2026</cYear>
173+
<unstructured_citation>astral-sh. (2026). Ruff (Version 0.15.5). https://github.com/astral-sh/ruff</unstructured_citation>
174+
</citation>
175+
<citation key="pylint">
176+
<article_title>Pylint</article_title>
177+
<author>pylint-dev</author>
178+
<cYear>2026</cYear>
179+
<unstructured_citation>pylint-dev. (2026). Pylint (Version 4.0.5). https://github.com/pylint-dev/pylint</unstructured_citation>
180+
</citation>
181+
</citation_list>
182+
</journal_article>
183+
</journal>
184+
</body>
185+
</doi_batch>

‎joss.10130/10.21105.joss.10130.pdf‎

291 KB
Binary file not shown.

0 commit comments

Comments
 (0)