Auto-differentiable Ensemble Kalman Filters

16 July 2021

Papers citing "Auto-differentiable Ensemble Kalman Filters"

25 / 25 papers shown

Title
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems Zhidi Lin Ying Li Feng Yin Juan Maroñas Alexandre Thiéry 49 0 0 24 Mar 2025
Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient Shaoqi Wang Chunjie Yang Siwei Lou 21 1 0 23 Sep 2024
Learning Optimal Filters Using Variational Inference Enoch Luk Eviatar Bach Ricardo Baptista Andrew Stuart 24 6 0 26 Jun 2024
CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation Chuanqi Chen Nan Chen Jin-Long Wu AI4CE 30 4 0 10 Apr 2024
Deep Generative Data Assimilation in Multimodal Setting Yongquan Qu Juan Nathaniel Shuolin Li Pierre Gentine 3DGS 26 14 0 10 Apr 2024
Regularization-Based Efficient Continual Learning in Deep State-Space Models Yuanhang Zhang Zhidi Lin Yiyong Sun Feng Yin Carsten Fritsche CLL 26 2 0 15 Mar 2024
Hybrid $^2$ Neural ODE Causal Modeling and an Application to Glycemic Response Bob Junyi Zou Matthew E. Levine D. Zaharieva Ramesh Johari Emily Fox 28 4 0 27 Feb 2024
Learning About Structural Errors in Models of Complex Dynamical Systems Jin-Long Wu Matthew E. Levine Tapio Schneider Andrew M. Stuart AI4CE 8 17 0 29 Dec 2023
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference Zhidi Lin Yiyong Sun Feng Yin Alexandre Thiéry 11 3 0 10 Dec 2023
Covariance Operator Estimation: Sparsity, Lengthscale, and Ensemble Kalman Filters Omar Al Ghattas Jiaheng Chen D. Sanz-Alonso Nathan Waniorek 11 4 0 25 Oct 2023
Enhancing State Estimation in Robots: A Data-Driven Approach with Differentiable Ensemble Kalman Filters Xinyu Liu Geoffrey Clark Joseph Campbell Yifan Zhou H. B. Amor 21 10 0 19 Aug 2023
Ensemble Kalman Filters with Resampling Omar Al Ghattas Jiajun Bao D. Sanz-Alonso 13 6 0 17 Aug 2023
Gradient-free training of neural ODEs for system identification and control using ensemble Kalman inversion Lucas Böttcher BDL 13 11 0 15 Jul 2023
Training neural operators to preserve invariant measures of chaotic attractors Ruoxi Jiang Peter Y. Lu Elena Orlova Rebecca Willett AI4TS 11 20 0 01 Jun 2023
Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates Ke Alexander Wang Matthew E. Levine Jiaxin Shi E. Fox 12 3 0 27 Apr 2023
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review Sibo Cheng César Quilodrán-Casas Said Ouala A. Farchi Che Liu ... Weiping Ding Yike Guo A. Carrassi Marc Bocquet Rossella Arcucci AI4CE 24 118 0 18 Mar 2023
Reduced-Order Autodifferentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 26 8 0 27 Jan 2023
Quantum Mechanics for Closure of Dynamical Systems D. Freeman D. Giannakis J. Slawinska 14 4 0 05 Aug 2022
Non-Asymptotic Analysis of Ensemble Kalman Updates: Effective Dimension and Localization Omar Al Ghattas D. Sanz-Alonso 20 12 0 05 Aug 2022
Hierarchical Ensemble Kalman Methods with Sparsity-Promoting Generalized Gamma Hyperpriors Hwanwoo Kim D. Sanz-Alonso A. Strang 20 6 0 19 May 2022
Discrepancy Modeling Framework: Learning missing physics, modeling systematic residuals, and disambiguating between deterministic and random effects Megan R. Ebers K. Steele J. Nathan Kutz 18 15 0 10 Mar 2022
A Framework for Machine Learning of Model Error in Dynamical Systems Matthew E. Levine Andrew M. Stuart 8 65 0 14 Jul 2021
Data Assimilation Networks Pierre Boudier Anthony Fillion Serge Gratton S. Gürol Sixin Zhang AI4CE 17 9 0 19 Oct 2020
Model error covariance estimation in particle and ensemble Kalman filters using an online expectation-maximization algorithm T. Cocucci M. Pulido M. Lucini P. Tandeo 28 11 0 04 Mar 2020
A Bayesian adaptive ensemble Kalman filter for sequential state and parameter estimation Jonathan R. Stroud Matthias Katzfuss C. Wikle 31 55 0 11 Nov 2016