Nikolas Kantas
On particle methods for parameter estimation in state-space models
N Kantas, A Doucet, SS Singh, J Maciejowski, N Chopin
Statistical science 30 (3), 328-351, 2015
An overview of sequential Monte Carlo methods for parameter estimation in general state-space models
N Kantas, A Doucet, SS Singh, JM Maciejowski
IFAC Proceedings Volumes 42 (10), 774-785, 2009
Sequential Monte Carlo methods for high-dimensional inverse problems: A case study for the Navier--Stokes equations
N Kantas, A Beskos, A Jasra
SIAM/ASA Journal on Uncertainty Quantification 2 (1), 464-489, 2014
On the convergence of adaptive sequential Monte Carlo methods
A Beskos, A Jasra, N Kantas, A Thiery
The Annals of Applied Probability 26 (2), 1111-1146, 2016
Simulation-based optimal sensor scheduling with application to observer trajectory planning
SS Singh, N Kantas, BN Vo, A Doucet, RJ Evans
Automatica 43 (5), 817-830, 2007
Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England
ES Knock, LK Whittles, JA Lees, PN Perez-Guzman, R Verity, RG FitzJohn, ...
Science Translational Medicine 13 (602), eabg4262, 2021
Distributed maximum likelihood for simultaneous self-localization and tracking in sensor networks
N Kantas, SS Singh, A Doucet
IEEE Transactions on Signal Processing 60 (10), 5038-5047, 2012
Sequential Monte Carlo for model predictive control
N Kantas, JM Maciejowski, A Lecchini-Visintini
Nonlinear model predictive control, 263-273, 2009
Simulation‐based Bayesian optimal design of aircraft trajectories for air traffic management
N Kantas, A Lecchini‐Visintini, JM Maciejowski
International Journal of Adaptive Control and Signal Processing 24 (10), 882-899, 2010
Gradient free parameter estimation for hidden Markov models with intractable likelihoods
E Ehrlich, A Jasra, N Kantas
Methodology and Computing in Applied Probability 17 (2), 315-349, 2015
Particle filtering for stochastic Navier--Stokes signal observed with linear additive noise
FP Llopis, N Kantas, A Beskos, A Jasra
SIAM Journal on Scientific Computing 40 (3), A1544-A1565, 2018
Linear variance bounds for particle approximations of time-homogeneous Feynman–Kac formulae
N Whiteley, N Kantas, A Jasra
Stochastic Processes and their Applications 122 (4), 1840-1865, 2012
Parameter estimation for the McKean-Vlasov stochastic differential equation
L Sharrock, N Kantas, P Parpas, GA Pavliotis
arXiv preprint arXiv:2106.13751, 2021
Approximate inference for observation-driven time series models with intractable likelihoods
A Jasra, N Kantas, E Ehrlich
ACM Transactions on Modeling and Computer Simulation (TOMACS) 24 (3), 1-25, 2014
On stochastic mirror descent with interacting particles: convergence properties and variance reduction
A Borovykh, N Kantas, P Parpas, GA Pavliotis
Physica D: Nonlinear Phenomena 418, 132844, 2021
Score-based parameter estimation for a class of continuous-time state space models
A Beskos, D Crisan, A Jasra, N Kantas, H Ruzayqat
SIAM Journal on Scientific Computing 43 (4), A2555-A2580, 2021
Stability of model predictive control using Markov chain Monte Carlo optimisation
E Siva, P Goulart, J Maciejowski, N Kantas
2009 European Control Conference (ECC), 2851-2856, 2009
Calculating principal eigen-functions of non-negative integral kernels: particle approximations and applications
N Whiteley, N Kantas
Mathematics of Operations Research 42 (4), 1007-1034, 2017
Sequential decision making in general state space models
N Kantas
University of Cambridge, 2009
On the generalised Langevin equation for simulated annealing
M Chak, N Kantas, GA Pavliotis
arXiv preprint arXiv:2003.06448, 2020
Системата не може да изпълни операцията сега. Опитайте отново по-късно.
Статии 1–20