O’Gorman, Eoin J (2022) Machine learning ecological networks. Science, 377 (6609). pp. 918-919. DOI https://doi.org/10.1126/science.add7563
O’Gorman, Eoin J (2022) Machine learning ecological networks. Science, 377 (6609). pp. 918-919. DOI https://doi.org/10.1126/science.add7563
O’Gorman, Eoin J (2022) Machine learning ecological networks. Science, 377 (6609). pp. 918-919. DOI https://doi.org/10.1126/science.add7563
Abstract
<jats:p>Deep-learning tools can help to construct historical, modern-day, and future food webs</jats:p>
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Animals; Food Chain; Deep Learning |
| Divisions: | Faculty of Science and Health Faculty of Science and Health > Life Sciences, School of |
| SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
| Depositing User: | Unnamed user with email elements@essex.ac.uk |
| Date Deposited: | 31 May 2023 13:10 |
| Last Modified: | 31 May 2023 13:11 |
| URI: | http://repository.essex.ac.uk/id/eprint/34159 |
Available files
Filename: add7563_O'Gorman_accepted.doc
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