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Interpretable inference of collective models from trajectory data with two-stage rule learning
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| Published in: | Complex & Intelligent Systems |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| _version_ | 1871650362399653889 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Complex & Intelligent Systems |
| description | |
| discipline_display | Computer Science |
| discipline_facet | Computer Science |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:106392 |
| institution | FRELIP |
| journal_source_facet | Complex & Intelligent Systems |
| last_indexed | 2026-07-25T02:01:18.564Z |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | Interpretable inference of collective models from trajectory data with two-stage rule learning Computer Science General Computer Science |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Computer Science General Computer Science Computer Science General Computer Science |
| subject_facet | Computer Science General Computer Science |
| title | Interpretable inference of collective models from trajectory data with two-stage rule learning |
| title_auth | Interpretable inference of collective models from trajectory data with two-stage rule learning |
| title_full | Interpretable inference of collective models from trajectory data with two-stage rule learning |
| title_fullStr | Interpretable inference of collective models from trajectory data with two-stage rule learning |
| title_full_unstemmed | Interpretable inference of collective models from trajectory data with two-stage rule learning |
| title_short | Interpretable inference of collective models from trajectory data with two-stage rule learning |
| title_sort | interpretable inference of collective models from trajectory data with two-stage rule learning |
| topic | Computer Science General Computer Science |
| url | https://link.springer.com/article/10.1007/s40747-026-02443-9 |