Cargando…
Combining data and theory for derivable scientific discovery with AI-Descartes
Scientists aim to discover meaningful formulae that accurately describe experimental data. Mathematical models of natural phenomena can be manually created from domain knowledge and fitted to data, or, in contrast, created automatically from large datasets with machine-learning algorithms. The probl...
Autores principales: | Cornelio, Cristina, Dash, Sanjeeb, Austel, Vernon, Josephson, Tyler R., Goncalves, Joao, Clarkson, Kenneth L., Megiddo, Nimrod, El Khadir, Bachir, Horesh, Lior |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10097814/ https://www.ncbi.nlm.nih.gov/pubmed/37045814 http://dx.doi.org/10.1038/s41467-023-37236-y |
Ejemplares similares
-
The AI for Scientific Discovery Network(+)
por: Kanza, Samantha, et al.
Publicado: (2021) -
Descartes /
por: Brunschvicg, Léon, 1869-1944
Publicado: (1939) -
Descartes /
por: Hoffmann, Abraham
Publicado: (1932) -
Descartes /
por: Fouillée, Alfred, 1838-1912
Publicado: (1944) -
Descartes
Publicado: (1998)