Cargando…
Discovery of Physics From Data: Universal Laws and Discrepancies
Machine learning (ML) and artificial intelligence (AI) algorithms are now being used to automate the discovery of physics principles and governing equations from measurement data alone. However, positing a universal physical law from data is challenging without simultaneously proposing an accompanyi...
Autores principales: | de Silva, Brian M., Higdon, David M., Brunton, Steven L., Kutz, J. Nathan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861345/ https://www.ncbi.nlm.nih.gov/pubmed/33733144 http://dx.doi.org/10.3389/frai.2020.00025 |
Ejemplares similares
-
Data-Driven Discovery of Mathematical and Physical Relations in Oncology Data Using Human-Understandable Machine Learning
por: Kurz, Daria, et al.
Publicado: (2021) -
Integrated Evolutionary Learning: An Artificial Intelligence Approach to Joint Learning of Features and Hyperparameters for Optimized, Explainable Machine Learning
por: de Lacy, Nina, et al.
Publicado: (2022) -
Argumentation and explanation in the law
por: Rotolo, Antonino, et al.
Publicado: (2023) -
Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing
por: Tripathi, Shailesh, et al.
Publicado: (2021) -
An intelligence coordination system toward creating the super-intelligent law firm
por: Kaomea, Peter
Publicado: (2023)