Modelling the longevity of complex living systems
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866909335339139072 |
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| author | Žliobaitė, Indrė |
| author_facet | Žliobaitė, Indrė |
| contents | This extended abstract was presented at the Nectar Track of ECML PKDD 2024 in Vilnius, Lithuania. The content supplements a recently published paper "Laws of Macroevolutionary Expansion" in the Proceedings of the National Academy of Sciences (PNAS). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_02838 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Modelling the longevity of complex living systems Žliobaitė, Indrė Populations and Evolution Machine Learning Quantitative Methods Applications This extended abstract was presented at the Nectar Track of ECML PKDD 2024 in Vilnius, Lithuania. The content supplements a recently published paper "Laws of Macroevolutionary Expansion" in the Proceedings of the National Academy of Sciences (PNAS). |
| title | Modelling the longevity of complex living systems |
| topic | Populations and Evolution Machine Learning Quantitative Methods Applications |
| url | https://arxiv.org/abs/2410.02838 |