Cargando…
Parsimonious neural networks learn interpretable physical laws
Machine learning is playing an increasing role in the physical sciences and significant progress has been made towards embedding domain knowledge into models. Less explored is its use to discover interpretable physical laws from data. We propose parsimonious neural networks (PNNs) that combine neura...
Autores principales: | Desai, Saaketh, Strachan, Alejandro |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8211802/ https://www.ncbi.nlm.nih.gov/pubmed/34140609 http://dx.doi.org/10.1038/s41598-021-92278-w |
Ejemplares similares
-
The law of therapeutic parsimony
por: Kalra, Sanjay, et al.
Publicado: (2016) -
Parsimonious Optimization of Multitask Neural Network Hyperparameters
por: Valsecchi, Cecile, et al.
Publicado: (2021) -
Sim2Ls: FAIR simulation workflows and data
por: Hunt, Martin, et al.
Publicado: (2022) -
Maximum parsimony interpretation of chromatin capture experiments
por: Homouz, Dirar, et al.
Publicado: (2019) -
Maximum Parsimony on Phylogenetic networks
por: Kannan, Lavanya, et al.
Publicado: (2012)