Research graph
References from Nonlinear Latent-Space Data Assimilation for Sea Surface Height Reconstruction from Sparse Observations. Local targets link to admitted publications; unresolved targets remain external evidence.
Kuroshio intrusion into the South China Sea: A review
10.1016/j.pocean.2014.05.012 · 2015 · External reference
10.5194/egusphere-egu21-14961
10.5194/egusphere-egu21-14961 · External reference
4DVarNet-SSH: End-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry
10.5194/gmd-16-2119-2023 · 2023 · External reference
Learning sea surface height interpolation from multivariate simulated satellite observations
10.1029/2023ms004047 · 2024 · External reference
Integrating wide-swath altimetry data into Level-4 multi-mission maps
10.5194/os-21-63-2025 · 2025 · External reference
A new approach to linear filtering and prediction problems
10.1115/1.3662552 · 1960 · External reference
Analysis methods for numerical weather prediction
10.1002/qj.49711247414 · 1986 · External reference
Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics
10.1029/94jc00572 · 1994 · External reference
An ensemble adjustment Kalman filter for data assimilation
10.1175/1520-0493(2001)129<2884:aeakff>2.0.co;2 · 2001 · External reference
Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects
10.1175/1520-0493(2001)129<0420:aswtet>2.0.co;2 · 2001 · External reference
Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter
10.1016/j.physd.2006.11.008 · 2007 · External reference
Data assimilation in the geosciences: An overview of methods, issues, and perspectives
10.1002/wcc.535 · 2018 · External reference
Beyond Gaussian statistical modeling in geophysical data assimilation
10.1175/2010mwr3164.1 · 2010 · External reference
Data assimilation challenges posed by nonlinear operators: A comparative study of ensemble and variational filters and smoothers
2021 · External reference
On sequential Monte Carlo sampling methods for Bayesian filtering
10.1023/a:1008935410038 · 2000 · External reference
A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
10.1109/78.978374 · 2002 · External reference
Obstacles to high-dimensional particle filtering
10.1175/2008mwr2529.1 · 2008 · External reference
Nonlinear data assimilation in geosciences: An extremely efficient particle filter
10.1002/qj.699 · 2010 · External reference
Weighted ensemble transform Kalman filter for image assimilation
10.3402/tellusa.v65i0.18803 · 2013 · External reference
Bridging the ensemble Kalman and particle filters
10.1093/biomet/ast020 · 2013 · External reference
A local ensemble transform Kalman particle filter for convective-scale data assimilation
10.1002/qj.3116 · 2018 · External reference
Data assimilation for nonlinear systems with a localized weighted ensemble transform Kalman filter
10.1002/qj.70097 · 2026 · External reference
Reducing the dimensionality of data with neural networks
10.1126/science.1127647 · 2006 · External reference
Improving the assimilation ability for the extreme events by proposing a nonlinear machine learning data assimilation approach
10.1029/2025gl118319 · 2025 · External reference
Learning variational data assimilation models and solvers
10.1029/2021ms002572 · 2021 · External reference
Combining data assimilation and machine learning to infer unresolved scale parametrization
10.1098/rsta.2020.0086 · 2021 · External reference
Machine learning with data assimilation and uncertainty quantification for dynamical systems: A review
10.1109/jas.2023.123537 · 2023 · External reference
Attention-based convolutional autoencoders for 3D-variational data assimilation
10.1016/j.cma.2020.113291 · 2020 · External reference
Latent space data assimilation by using deep learning
10.1002/qj.4153 · 2021 · External reference
Efficient high-dimensional variational data assimilation with machine-learned reduced-order models
10.5194/gmd-15-3433-2022 · 2022 · External reference
Generalised latent assimilation in heterogeneous reduced spaces with machine learning surrogate models
10.1007/s10915-022-02059-4 · 2023 · External reference
Multi-domain encoder-decoder neural networks for latent data assimilation in dynamical systems
10.1016/j.cma.2024.117201 · 2024 · External reference
3D-Var data assimilation using a variational autoencoder
10.1002/qj.4708 · 2024 · External reference
Ensemble Kalman filter in latent space using a variational autoencoder pair
10.1002/qj.70070 · 2026 · External reference
A novel latent space data assimilation framework with autoencoder-observation to latent space (AE-O2L) network. Part I: The observation-only analysis method
10.1175/mwr-d-24-0057.1 · 2025 · External reference
A novel latent space data assimilation framework with autoencoder-observation to latent space (AE-O2L) network. Part II: Observation and background assimilation with interpretability
10.1175/mwr-d-24-0058.1 · 2025 · External reference
Physically consistent global atmospheric data assimilation with machine learning in latent space
10.1126/sciadv.aea4248 · 2026 · External reference
Latent data assimilation with non-explicit observation operator in hydrology
10.1002/qj.5009 · 2025 · External reference
Unresolved reference
External reference
The deep latent space particle filter for real-time data assimilation with uncertainty quantification
10.1038/s41598-024-69901-7 · 2024 · External reference
Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter
10.1175/1520-0493(2001)129<2776:ddfobe>2.0.co;2 · 2001 · External reference
Can local particle filters beat the curse of dimensionality?
10.1214/14-aap1061 · 2015 · External reference
Separating fast and slow modes in coupled chaotic systems
10.5194/npg-11-319-2004 · 2004 · External reference
Deterministic nonperiodic flow
10.1175/1520-0469(1963)020<0130:dnf>2.0.co;2 · 1963 · External reference
Unresolved reference
External reference
A local ensemble transform Kalman particle filter for convective-scale data assimilation
10.1002/qj.3116 · ExternalCitation · doi-reference
Latent space data assimilation by using deep learning
10.1002/qj.4153 · ExternalCitation · doi-reference
3D-Var data assimilation using a variational autoencoder
10.1002/qj.4708 · ExternalCitation · doi-reference
Analysis methods for numerical weather prediction
10.1002/qj.49711247414 · ExternalCitation · doi-reference
Latent data assimilation with non-explicit observation operator in hydrology
10.1002/qj.5009 · ExternalCitation · doi-reference
Nonlinear data assimilation in geosciences: An extremely efficient particle filter
10.1002/qj.699 · ExternalCitation · doi-reference
Ensemble Kalman filter in latent space using a variational autoencoder pair
10.1002/qj.70070 · ExternalCitation · doi-reference
Data assimilation for nonlinear systems with a localized weighted ensemble transform Kalman filter
10.1002/qj.70097 · ExternalCitation · doi-reference
Data assimilation in the geosciences: An overview of methods, issues, and perspectives
10.1002/wcc.535 · ExternalCitation · doi-reference
Generalised latent assimilation in heterogeneous reduced spaces with machine learning surrogate models
10.1007/s10915-022-02059-4 · ExternalCitation · doi-reference
Attention-based convolutional autoencoders for 3D-variational data assimilation
10.1016/j.cma.2020.113291 · ExternalCitation · doi-reference
Multi-domain encoder-decoder neural networks for latent data assimilation in dynamical systems
10.1016/j.cma.2024.117201 · ExternalCitation · doi-reference
Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter
10.1016/j.physd.2006.11.008 · ExternalCitation · doi-reference
Kuroshio intrusion into the South China Sea: A review
10.1016/j.pocean.2014.05.012 · ExternalCitation · doi-reference
On sequential Monte Carlo sampling methods for Bayesian filtering
10.1023/a:1008935410038 · ExternalCitation · doi-reference
Learning variational data assimilation models and solvers
10.1029/2021ms002572 · ExternalCitation · doi-reference
Learning sea surface height interpolation from multivariate simulated satellite observations
10.1029/2023ms004047 · ExternalCitation · doi-reference
Improving the assimilation ability for the extreme events by proposing a nonlinear machine learning data assimilation approach
10.1029/2025gl118319 · ExternalCitation · doi-reference
Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics
10.1029/94jc00572 · ExternalCitation · doi-reference
The deep latent space particle filter for real-time data assimilation with uncertainty quantification
10.1038/s41598-024-69901-7 · ExternalCitation · doi-reference
Bridging the ensemble Kalman and particle filters
10.1093/biomet/ast020 · ExternalCitation · doi-reference
Combining data assimilation and machine learning to infer unresolved scale parametrization
10.1098/rsta.2020.0086 · ExternalCitation · doi-reference
A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
10.1109/78.978374 · ExternalCitation · doi-reference
Machine learning with data assimilation and uncertainty quantification for dynamical systems: A review
10.1109/jas.2023.123537 · ExternalCitation · doi-reference
A new approach to linear filtering and prediction problems
10.1115/1.3662552 · ExternalCitation · doi-reference
Physically consistent global atmospheric data assimilation with machine learning in latent space
10.1126/sciadv.aea4248 · ExternalCitation · doi-reference
Reducing the dimensionality of data with neural networks
10.1126/science.1127647 · ExternalCitation · doi-reference
Deterministic nonperiodic flow
10.1175/1520-0469(1963)020<0130:dnf>2.0.co;2 · ExternalCitation · doi-reference
Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects
10.1175/1520-0493(2001)129<0420:aswtet>2.0.co;2 · ExternalCitation · doi-reference
Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter
10.1175/1520-0493(2001)129<2776:ddfobe>2.0.co;2 · ExternalCitation · doi-reference
An ensemble adjustment Kalman filter for data assimilation
10.1175/1520-0493(2001)129<2884:aeakff>2.0.co;2 · ExternalCitation · doi-reference
Obstacles to high-dimensional particle filtering
10.1175/2008mwr2529.1 · ExternalCitation · doi-reference
Beyond Gaussian statistical modeling in geophysical data assimilation
10.1175/2010mwr3164.1 · ExternalCitation · doi-reference
A novel latent space data assimilation framework with autoencoder-observation to latent space (AE-O2L) network. Part I: The observation-only analysis method
10.1175/mwr-d-24-0057.1 · ExternalCitation · doi-reference
A novel latent space data assimilation framework with autoencoder-observation to latent space (AE-O2L) network. Part II: Observation and background assimilation with interpretability
10.1175/mwr-d-24-0058.1 · ExternalCitation · doi-reference
Can local particle filters beat the curse of dimensionality?
10.1214/14-aap1061 · ExternalCitation · doi-reference
Weighted ensemble transform Kalman filter for image assimilation
10.3402/tellusa.v65i0.18803 · ExternalCitation · doi-reference
10.5194/egusphere-egu21-14961
10.5194/egusphere-egu21-14961 · ExternalCitation · doi-reference
Efficient high-dimensional variational data assimilation with machine-learned reduced-order models
10.5194/gmd-15-3433-2022 · ExternalCitation · doi-reference
4DVarNet-SSH: End-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry
10.5194/gmd-16-2119-2023 · ExternalCitation · doi-reference
Separating fast and slow modes in coupled chaotic systems
10.5194/npg-11-319-2004 · ExternalCitation · doi-reference
Integrating wide-swath altimetry data into Level-4 multi-mission maps
10.5194/os-21-63-2025 · ExternalCitation · doi-reference
