Christopher Nemeth
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Sequential Monte Carlo methods for state and parameter estimation in abruptly changing environments
C Nemeth, P Fearnhead, L Mihaylova
IEEE Transactions on Signal Processing 62 (5), 1245-1255, 2014
712014
Particle approximations of the score and observed information matrix for parameter estimation in state–space models with linear computational cost
C Nemeth, P Fearnhead, L Mihaylova
Journal of Computational and Graphical Statistics 25 (4), 1138-1157, 2016
60*2016
Control variates for stochastic gradient MCMC
J Baker, P Fearnhead, EB Fox, C Nemeth
Statistics and Computing 29 (3), 599-615, 2019
542019
Particle Metropolis-adjusted Langevin algorithms
C Nemeth, C Sherlock, P Fearnhead
Biometrika 103 (3), 701-717, 2016
27*2016
Merging MCMC subposteriors through Gaussian-process approximations
C Nemeth, C Sherlock
Bayesian Analysis 13 (2), 507-530, 2018
212018
Particle learning methods for state and parameter estimation
C Nemeth, P Fearnhead, L Mihaylova, D Vorley
9th IET Data Fusion and Target Tracking Conference, London, U.K., 2012
112012
Pseudo-extended markov chain monte carlo
C Nemeth, F Lindsten, M Filippone, J Hensman
Advances in Neural Information Processing Systems, 4312-4322, 2019
82019
Stochastic gradient markov chain monte carlo
C Nemeth, P Fearnhead
arXiv preprint arXiv:1907.06986, 2019
72019
sgmcmc: An R package for stochastic gradient Markov chain Monte Carlo
J Baker, P Fearnhead, EB Fox, C Nemeth
Journal of Statistical Software 91 (1), 1-27, 2019
52019
GaussianProcesses. jl: A Nonparametric Bayes package for the Julia Language
J Fairbrother, C Nemeth, M Rischard, J Brea, T Pinder
arXiv preprint arXiv:1812.09064, 2018
52018
Stochastic gradient mcmc for nonlinear state space models
C Aicher, S Putcha, C Nemeth, P Fearnhead, EB Fox
arXiv preprint arXiv:1901.10568, 2019
42019
Large-Scale Stochastic Sampling from the Probability Simplex
J Baker, P Fearnhead, EB Fox, C Nemeth
Advances in Neural Information Processing Systems 31, 6720-6730, 2018
42018
Parameter estimation for state space models using sequential Monte Carlo algorithms
C Nemeth
Lancaster University, 2014
32014
Bearings-only tracking with particle filtering for joint parameter learning and state estimation
C Nemeth, P Fearnhead, L Mihaylova, D Vorley
2012 15th International Conference on Information Fusion, 824-831, 2012
32012
Semi-Exact Control Functionals From Sard's Method
LF South, T Karvonen, C Nemeth, M Girolami, C Oates
arXiv preprint arXiv:2002.00033, 2020
22020
Bayesian calibration of firn densification models
V Verjans, AA Leeson, C Nemeth, CM Stevens, P Kuipers Munneke, ...
The Cryosphere 14 (9), 3017-3032, 2020
12020
Latent space representations of hypergraphs
K Turnbull, S Lunagómez, C Nemeth, E Airoldi
arXiv preprint arXiv:1909.00472, 2019
12019
Parameter estimation with Particle Filtering Algorithms
E Zanini, C Nemeth, HMM HMMs
STOR-i Internship 2012, Lancaster University, 2012
12012
Telling the Researcher STOR-i With Data Science: Elsevier data scientists are working with Lancaster University researchers to advance our understanding of researcher behaviors
G Bolt, H Muncey, S Lunagomez Coria, C Nemeth
2020
Discussion of" Unbiased Markov chain Monte Carlo with couplings" by Pierre E. Jacob, John O'Leary and Yves F. Atchad\'e
LF South, C Nemeth, CJ Oates
arXiv preprint arXiv:1912.10496, 2019
2019
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Artiklar 1–20