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| Published in: | Journal of Open Source Software |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| Subjects: | |
| Tags: |
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| _version_ | 1864030190457323520 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Journal of Open Source Software |
| description | |
| discipline_display | Engineering & Technology |
| discipline_facet | Engineering & Technology |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:7514 |
| institution | FRELIP |
| journal_source_facet | Journal of Open Source Software |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | itwinai: A Python Toolkit for Scalable Scientific Machine Learning on HPC Systems Computer Science & Information Science Computer Science & IT Engineering & Technology |
| sub_discipline_display | Computer Science & IT |
| sub_discipline_facet | Computer Science & IT |
| subject_display | Computer Science & Information Science Computer Science & IT Engineering & Technology Computer Science & Information Science Computer Science & IT Engineering & Technology |
| subject_facet | Computer Science & Information Science Computer Science & IT Engineering & Technology |
| title | itwinai: A Python Toolkit for Scalable Scientific Machine Learning on HPC Systems |
| title_auth | itwinai: A Python Toolkit for Scalable Scientific Machine Learning on HPC Systems |
| title_full | itwinai: A Python Toolkit for Scalable Scientific Machine Learning on HPC Systems |
| title_fullStr | itwinai: A Python Toolkit for Scalable Scientific Machine Learning on HPC Systems |
| title_full_unstemmed | itwinai: A Python Toolkit for Scalable Scientific Machine Learning on HPC Systems |
| title_short | itwinai: A Python Toolkit for Scalable Scientific Machine Learning on HPC Systems |
| title_sort | itwinai: a python toolkit for scalable scientific machine learning on hpc systems |
| topic | Computer Science & Information Science Computer Science & IT Engineering & Technology |
| url | https://joss.theoj.org/papers/10.21105/joss.09409 |