11 citations as recorded by crossref.

1. Inference solves a boundary-value collision problem with relevance to neutrino flavor transformation E. Armstrong https://doi.org/10.1103/PhysRevD.105.083012
2. Leveraging neutrino flavor physics for supernova model differentiation L. Newkirk et al. https://doi.org/10.1103/PhysRevD.111.063027
3. Long short-term memory embedded nudging schemes for nonlinear data assimilation of geophysical flows S. Pawar et al. https://doi.org/10.1063/5.0012853
4. Inference offers a metric to constrain dynamical models of neutrino flavor transformation E. Armstrong et al. https://doi.org/10.1103/PhysRevD.102.043013
5. Inference of bipolar neutrino flavor oscillations near a core-collapse supernova based on multiple measurements at Earth E. Armstrong et al. https://doi.org/10.1103/PhysRevD.105.103003
6. Identifying the measurements required to estimate rates of COVID-19 transmission, infection, and detection, using variational data assimilation E. Armstrong et al. https://doi.org/10.1016/j.idm.2020.10.010
7. Predicting the Behavior of Sparsely-Sampled Systems Across Neurobiology and Epidemiology E. Armstrong https://doi.org/10.1007/s11538-023-01176-x
8. Inference finds consistency between a neutrino flavor evolution model and Earth-based solar neutrino measurements C. Laber-Smith et al. https://doi.org/10.1103/PhysRevD.107.023013
9. Constraining solar electron number density via neutrino flavor data at Borexino C. Laber-Smith et al. https://doi.org/10.1103/PhysRevD.110.043011
10. Statistical data assimilation for estimating electrophysiology simultaneously with connectivity within a biological neuronal network E. Armstrong https://doi.org/10.1103/PhysRevE.101.012415
11. Mathematical foundations of hybrid data assimilation from a synchronization perspective S. Penny https://doi.org/10.1063/1.5001819