3 papers
stat.ME2026
Statistical Tapers for Correlation-Based Localization in Ensemble Data Assimilation
Alexandre A. Emerick, Vinicius Luiz Santos Silva
Localization is essential in ensemble-based data assimilation because finite ensembles produce noisy covariance estimates, causing spurious updates and excessive loss of ensemble v…
cs.LG2025
Integrating Score-Based Diffusion Models with Machine Learning-Enhanced Localization for Advanced Data Assimilation in Geological Carbon Storage
Gabriel Serrão Seabra, Nikolaj T. Mücke, Vinicius Luiz Santos Silva +3
Accurate characterization of subsurface heterogeneity is important for the safe and effective implementation of geological carbon storage (GCS) projects. This paper explores how ma…
cs.LG2025
Mitigating loss of variance in ensemble data assimilation: machine learning-based and distance-free localization
Vinicius L. S. Silva, Gabriel S. Seabra, Alexandre A. Emerick
We propose two new methods based/inspired by machine learning for tabular data and distance-free localization to enhance the covariance estimations in an ensemble data assimilation…