An Ensemble Information Filter: Learning and Encoding Sparse Structures in Ensemble Kalman Methods
集成信息滤波：在集成卡尔曼方法中学习与编码稀疏结构
Ensemble-based Data Assimilation faces significant challenges in high-dimensional systems due to spurious correlations and ensemble collapse. We propose the Ensemble Information Filter, which addresses these issues by encoding locality directly in the precision matrix through sparse Markov structure. This approach is motivated by connections to SPDE-based models, where local operators induce sparse precision representations and provide a principled form of regularisation.…