Ensemble Kalman inversion: mean-field limit and convergence analysis

DOI10.1007/s11222-020-09976-0zbMath1462.62023arXiv1908.05575OpenAlexW3121011245MaRDI QIDQ2029092

Zhiyan Ding, Qin Li

Publication date: 3 June 2021

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1908.05575

zbMATH Keywords

Fokker-Planck equationWasserstein metricmean-field limitensemble Kalman inversion

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Related Items (16)

Continuous Time Limit of the Stochastic Ensemble Kalman Inversion: Strong Convergence Analysis ⋮ Recent trends on nonlinear filtering for inverse problems ⋮ Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion ⋮ Constrained ensemble Langevin Monte Carlo ⋮ A Stabilization of a Continuous Limit of the Ensemble Kalman Inversion ⋮ Iterated Kalman methodology for inverse problems ⋮ Localized ensemble Kalman inversion ⋮ Markov chain generative adversarial neural networks for solving Bayesian inverse problems in physics applications ⋮ Complete Deterministic Dynamics and Spectral Decomposition of the Linear Ensemble Kalman Inversion ⋮ Adaptive Ensemble Kalman Inversion with Statistical Linearization ⋮ Filtering Methods for Coupled Inverse Problems ⋮ Subsampling in ensemble Kalman inversion ⋮ Rough McKean-Vlasov dynamics for robust ensemble Kalman filtering ⋮ Ensemble Kalman inversion for nonlinear problems: weights, consistency, and variance bounds ⋮ Propagation of chaos: a review of models, methods and applications. II: Applications ⋮ Gradient flow structure and convergence analysis of the ensemble Kalman inversion for nonlinear forward models

Uses Software

• EnKF

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• On the rate of convergence in Wasserstein distance of the empirical measure
• A dynamical systems framework for intermittent data assimilation
• Kinetic methods for inverse problems
• Deterministic Mean-Field Ensemble Kalman Filtering
• Ensemble Kalman methods for inverse problems
• STOCHASTIC MEAN-FIELD LIMIT: NON-LIPSCHITZ FORCES AND SWARMING
• Inverse problems: A Bayesian perspective
• A WELL-POSEDNESS THEORY IN MEASURES FOR SOME KINETIC MODELS OF COLLECTIVE MOTION
• Analysis of the Ensemble and Polynomial Chaos Kalman Filters in Bayesian Inverse Problems
• A Strongly Convergent Numerical Scheme from Ensemble Kalman Inversion
• Scaling Limit of the Stein Variational Gradient Descent: The Mean Field Regime
• Convergence analysis of ensemble Kalman inversion: the linear, noisy case
• Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler
• On the continuous time limit of the ensemble Kalman filter
• Well posedness and convergence analysis of the ensemble Kalman inversion
• Data assimilation: The Schrödinger perspective
• Analysis of the Ensemble Kalman Filter for Inverse Problems
• Data Assimilation

This page was built for publication: Ensemble Kalman inversion: mean-field limit and convergence analysis