Cargando…
Cluster-based network modeling—From snapshots to complex dynamical systems
We propose a universal method for data-driven modeling of complex nonlinear dynamics from time-resolved snapshot data without prior knowledge. Complex nonlinear dynamics govern many fields of science and engineering. Data-driven dynamic modeling often assumes a low-dimensional subspace or manifold f...
Autores principales: | Fernex, Daniel, Noack, Bernd R., Semaan, Richard |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208726/ https://www.ncbi.nlm.nih.gov/pubmed/34134987 http://dx.doi.org/10.1126/sciadv.abf5006 |
Ejemplares similares
-
Inferring Temporal Information from a Snapshot of a Dynamic Network
por: Sreedharan, Jithin K., et al.
Publicado: (2019) -
Inferring Centrality from Network Snapshots
por: Shao, Haibin, et al.
Publicado: (2017) -
Fundamental limits on dynamic inference from single-cell snapshots
por: Weinreb, Caleb, et al.
Publicado: (2018) -
High Sensitivity Snapshot Spectrometer Based on Deep Network Unmixing
por: Xie, Hui, et al.
Publicado: (2020) -
SnapShot: Embryo models
por: Rivron, Nicolas, et al.
Publicado: (2021)