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On Particle Methods for Parameter Estimation in State-Space Models

Statistical science, 2015-08, Vol.30 (3), p.328-351

2015

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ON THE CONVERGENCE OF ADAPTIVE SEQUENTIAL MONTE CARLO METHODS

The Annals of applied probability, 2016-04, Vol.26 (2), p.1111-1146

2016

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Sequential Monte Carlo Methods for High-Dimensional Inverse Problems: A Case Study for the Navier--Stokes Equations

SIAM/ASA journal on uncertainty quantification, 2014-01, Vol.2 (1), p.464-489

2014

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Joint Online Parameter Estimation and Optimal Sensor Placement for the Partially Observed Stochastic Advection-Diffusion Equation

SIAM/ASA journal on uncertainty quantification, 2022-01, Vol.10 (1), p.55-95

2022

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Unbiased estimation using a class of diffusion processes

Journal of computational physics, 2023-01, Vol.472, p.111643, Article 111643

2023

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Two-timescale stochastic gradient descent in continuous time with applications to joint online parameter estimation and optimal sensor placement

Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, 2023-05, Vol.29 (2)

2023

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Calculating Principal Eigen-Functions of Non-Negative Integral Kernels: Particle Approximations and Applications

Mathematics of operations research, 2017-11, Vol.42 (4), p.1007-1034

2017

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Online parameter estimation for the McKean–Vlasov stochastic differential equation

Stochastic processes and their applications, 2023-08, Vol.162, p.481-546

2023

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Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models

SIAM journal on scientific computing, 2021-01, Vol.43 (4), p.A2555-A2580

2021

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Some recent developments in Markov Chain Monte Carlo for cointegrated time series

ESAIM. Proceedings and surveys, 2017, Vol.59, p.76-103

2017

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Sequential Markov chain Monte Carlo for Lagrangian data assimilation with applications to unknown data locations

Quarterly journal of the Royal Meteorological Society, 2024-04, Vol.150 (761), p.2418-2439

2024

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Particle Filtering for Stochastic Navier--Stokes Signal Observed with Linear Additive Noise

SIAM journal on scientific computing, 2018-01, Vol.40 (3), p.A1544-A1565

2018

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On the Generalized Langevin Equation for Simulated Annealing

SIAM/ASA journal on uncertainty quantification, 2023-01, Vol.11 (1), p.139-167

2023

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Distributed Maximum Likelihood for Simultaneous Self-Localization and Tracking in Sensor Networks

IEEE transactions on signal processing, 2012-10, Vol.60 (10), p.5038-5047

2012

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Factor‐augmented Bayesian cointegration models: a case‐study on the soybean crush spread

Journal of the Royal Statistical Society Series C: Applied Statistics, 2020-04, Vol.69 (2), p.483-500

2020

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Optimal friction matrix for underdamped Langevin sampling

ESAIM: Mathematical Modelling and Numerical Analysis, 2023-11, Vol.57 (6), p.3335-3371

2023

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On adaptive estimation for dynamic Bernoulli bandits

Foundations of data science, 2019-06, Vol.1 (2), p.197-225

2019

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A Lagged Particle Filter for Stable Filtering of Certain High-Dimensional State-Space Models

SIAM/ASA journal on uncertainty quantification, 2022-09, Vol.10 (3), p.1130-1161

2022

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Gradient Free Parameter Estimation for Hidden Markov Models with Intractable Likelihoods

Methodology and computing in applied probability, 2015-06, Vol.17 (2), p.315-349

2015

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Linear variance bounds for particle approximations of time-homogeneous Feynman–Kac formulae

Stochastic processes and their applications, 2012-04, Vol.122 (4), p.1840-1865

2012

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Approximate Inference for Observation-Driven Time Series Models with Intractable Likelihoods

ACM transactions on modeling and computer simulation, 2014-05, Vol.24 (3), p.1-25

2014

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Bayesian parameter inference for partially observed stopped processes

Statistics and computing, 2014, Vol.24 (1), p.1-20

2014

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Sequential decision making in general state space models

Kantas, Nikolas

2009

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Bayesian Inference for Dynamic Cointegration Models with Application to Soybean Crush Spread

SSRN Electronic Journal

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On Particle Methods for Parameter Estimation in State-Space Models

ON THE CONVERGENCE OF ADAPTIVE SEQUENTIAL MONTE CARLO METHODS

Sequential Monte Carlo Methods for High-Dimensional Inverse Problems: A Case Study for the Navier--Stokes Equations

Joint Online Parameter Estimation and Optimal Sensor Placement for the Partially Observed Stochastic Advection-Diffusion Equation

Unbiased estimation using a class of diffusion processes

Two-timescale stochastic gradient descent in continuous time with applications to joint online parameter estimation and optimal sensor placement

Calculating Principal Eigen-Functions of Non-Negative Integral Kernels: Particle Approximations and Applications

Online parameter estimation for the McKean–Vlasov stochastic differential equation

Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models

Some recent developments in Markov Chain Monte Carlo for cointegrated time series

Sequential Markov chain Monte Carlo for Lagrangian data assimilation with applications to unknown data locations

Particle Filtering for Stochastic Navier--Stokes Signal Observed with Linear Additive Noise

On the Generalized Langevin Equation for Simulated Annealing

Distributed Maximum Likelihood for Simultaneous Self-Localization and Tracking in Sensor Networks

Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

Factor‐augmented Bayesian cointegration models: a case‐study on the soybean crush spread

Optimal friction matrix for underdamped Langevin sampling

On adaptive estimation for dynamic Bernoulli bandits

A Lagged Particle Filter for Stable Filtering of Certain High-Dimensional State-Space Models

Gradient Free Parameter Estimation for Hidden Markov Models with Intractable Likelihoods

Linear variance bounds for particle approximations of time-homogeneous Feynman–Kac formulae

Approximate Inference for Observation-Driven Time Series Models with Intractable Likelihoods

Bayesian parameter inference for partially observed stopped processes

Sequential decision making in general state space models

Bayesian Inference for Dynamic Cointegration Models with Application to Soybean Crush Spread

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