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A probabilistic scheme for joint parameter estimation and state
  prediction in complex dynamical systems
v1v2 (latest)

A probabilistic scheme for joint parameter estimation and state prediction in complex dynamical systems

11 August 2017
Sara Pérez-Vieites
I. P. Mariño
Joaquín Míguez
ArXiv (abs)PDFHTML

Papers citing "A probabilistic scheme for joint parameter estimation and state prediction in complex dynamical systems"

5 / 5 papers shown
Title
An overview of differentiable particle filters for data-adaptive
  sequential Bayesian inference
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference
Xiongjie Chen
Yunpeng Li
78
15
0
19 Feb 2023
Nested smoothing algorithms for inference and tracking of heterogeneous
  multi-scale state-space systems
Nested smoothing algorithms for inference and tracking of heterogeneous multi-scale state-space systems
Sara Pérez-Vieites
H. Molina-Bulla
Joaquín Míguez
50
0
0
16 Apr 2022
Nested Gaussian filters for recursive Bayesian inference and nonlinear
  tracking in state space models
Nested Gaussian filters for recursive Bayesian inference and nonlinear tracking in state space models
Sara Pérez-Vieites
Joaquín Míguez
65
10
0
23 Mar 2021
Bayesian equation selection on sparse data for discovery of stochastic
  dynamical systems
Bayesian equation selection on sparse data for discovery of stochastic dynamical systems
Kushagra Gupta
Dootika Vats
Snigdhansu Chatterjee
46
3
0
12 Jan 2021
A Kalman particle filter for online parameter estimation with
  applications to affine models
A Kalman particle filter for online parameter estimation with applications to affine models
Jian He
Asma Khedher
Peter Spreij
48
6
0
21 May 2019
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