| 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 | 471 | 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 | 311 | 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 | 107 | 2014 |
| On the convergence of adaptive sequential Monte Carlo methods A Beskos, A Jasra, N Kantas, A Thiery | 96 | 2016 |
| 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 | 82* | 2021 |
| 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 | 75 | 2007 |
| 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 | 69 | 2012 |
| Sequential Monte Carlo for model predictive control N Kantas, JM Maciejowski, A Lecchini-Visintini Nonlinear model predictive control: Towards new challenging applications …, 2009 | 63 | 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 | 30 | 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 | 27* | 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 | 24 | 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 | 19 | 2012 |
| Parameter estimation for the McKean-Vlasov stochastic differential equation L Sharrock, N Kantas, P Parpas, GA Pavliotis arXiv preprint arXiv:2106.13751, 2021 | 15 | 2021 |
| 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 | 12 | 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 | 12 | 2014 |
| 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 | 10 | 2021 |
| On the generalised Langevin equation for simulated annealing M Chak, N Kantas, GA Pavliotis arXiv preprint arXiv:2003.06448, 2020 | 10 | 2020 |
| 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 | 10 | 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 | 9* | 2017 |
| Sequential decision making in general state space models N Kantas University of Cambridge, 2009 | 9 | 2009 |
Sumeetpal Sidhu SinghTibra Foundation Chair in Mathematical Sciences, School of Mathematics, University of WollongongVerified email at uow.edu.au
