Feature-informed data assimilation
From MaRDI portal
Publication:6087915
DOI10.1016/J.JCP.2023.112499OpenAlexW4386813818MaRDI QIDQ6087915
Apoorv Srivastava, Wei Kang, Daniel M. Tartakovsky
Publication date: 16 November 2023
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jcp.2023.112499
Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx) Inference from stochastic processes (62Mxx) Stochastic systems and control (93Exx)
Cites Work
- Unnamed Item
- Unnamed Item
- Solving 1D conservation laws using Pontryagin's minimum principle
- Model and data reduction for data assimilation: particle filters employing projected forecasts and data with application to a shallow water model
- A metric tensor approach to data assimilation with adaptive moving meshes
- Information geometry of physics-informed statistical manifolds and its use in data assimilation
- Nonlinear data assimilation
- PyClaw: Accessible, Extensible, Scalable Tools for Wave Propagation Problems
- High Lewis Number Combustion Wavefronts: A Perturbative Melnikov Analysis
- A new method for the nonlinear transformation of means and covariances in filters and estimators
- Coupling Techniques for Nonlinear Ensemble Filtering
- Feedforward Neural Networks and Compositional Functions with Applications to Dynamical Systems
- Learning on dynamic statistical manifolds
- Data Assimilation
- Data Assimilation
- Data Assimilation
This page was built for publication: Feature-informed data assimilation