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Reduced-Order Autodifferentiable Ensemble Kalman Filters

Reduced-Order Autodifferentiable Ensemble Kalman Filters

27 January 2023
Yuming Chen
D. Sanz-Alonso
Rebecca Willett
ArXivPDFHTML

Papers citing "Reduced-Order Autodifferentiable Ensemble Kalman Filters"

10 / 10 papers shown
Title
Flow-based Bayesian filtering for high-dimensional nonlinear stochastic dynamical systems
Xintong Wang
Xiaofei Guan
Ling Guo
Hao Wu
BDL
43
0
0
22 Feb 2025
The Deep Latent Space Particle Filter for Real-Time Data Assimilation
  with Uncertainty Quantification
The Deep Latent Space Particle Filter for Real-Time Data Assimilation with Uncertainty Quantification
N. T. Mücke
Sander M. Bohté
C. Oosterlee
32
0
0
04 Jun 2024
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field
  and Online Inference
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference
Zhidi Lin
Yiyong Sun
Feng Yin
Alexandre Thiéry
16
4
0
10 Dec 2023
Ensemble Kalman Filters with Resampling
Ensemble Kalman Filters with Resampling
Omar Al Ghattas
Jiajun Bao
D. Sanz-Alonso
16
6
0
17 Aug 2023
Efficient Bayesian Physics Informed Neural Networks for Inverse Problems
  via Ensemble Kalman Inversion
Efficient Bayesian Physics Informed Neural Networks for Inverse Problems via Ensemble Kalman Inversion
Andrew Pensoneault
Xueyu Zhu
PINN
19
5
0
13 Mar 2023
Auto-differentiable Ensemble Kalman Filters
Auto-differentiable Ensemble Kalman Filters
Yuming Chen
D. Sanz-Alonso
Rebecca Willett
32
33
0
16 Jul 2021
Machine Learning Techniques to Construct Patched Analog Ensembles for
  Data Assimilation
Machine Learning Techniques to Construct Patched Analog Ensembles for Data Assimilation
L. Yang
Ian G. Grooms
13
18
0
27 Feb 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
203
2,272
0
18 Oct 2020
Combining Machine Learning with Knowledge-Based Modeling for Scalable
  Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal
  Systems
Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems
Alexander Wikner
Jaideep Pathak
Brian Hunt
M. Girvan
T. Arcomano
I. Szunyogh
Andrew Pomerance
Edward Ott
AI4CE
62
70
0
10 Feb 2020
A Bayesian adaptive ensemble Kalman filter for sequential state and
  parameter estimation
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
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