2 citations · 3 across the 2 of their papers we have counts for
6 papers
Multilevel Ensemble Kalman-Bucy Filters
Neil K. Chada, Ajay Jasra, Fangyuan Yu
In this article we consider the linear filtering problem in continuous-time. We develop and apply multilevel Monte Carlo (MLMC) strategies for ensemble Kalman-Bucy filters (EnKBFs)…
Iterative Ensemble Kalman Methods: A Unified Perspective with Some New Variants
Neil K. Chada, Yuming Chen, Daniel Sanz-Alonso
This paper provides a unified perspective of iterative ensemble Kalman methods, a family of derivative-free algorithms for parameter reconstruction and other related tasks. We iden…
Consistency analysis of bilevel data-driven learning in inverse problems
Neil K. Chada, Claudia Schillings, Xin T. Tong +1
One fundamental problem when solving inverse problems is how to find regularization parameters. This article considers solving this problem using data-driven bilevel optimization,…
Posterior Convergence Analysis of -Stable Sheets
Neil K. Chada, Sari Lasanen, Lassi Roininen
This paper is concerned with the theoretical understanding of -stable sheets on . Our motivation for this is in the context of Bayesian inverse problems, where…
Elements of asymptotic theory with outer probability measures
Jeremie Houssineau, Neil K. Chada, Emmanuel Delande
Outer measures can be used for statistical inference in place of probability measures to bring flexibility in terms of model specification. The corresponding statistical procedures…
On the Incorporation of Box-Constraints for Ensemble Kalman Inversion
Neil K. Chada, Claudia Schillings, Simon Weissmann
The Bayesian approach to inverse problems is widely used in practice to infer unknown parameters from noisy observations. In this framework, the ensemble Kalman inversion has been…