Fetching the paper…
Reading the bibliography…
Particle filters contain the promise of fully nonlinear data assimilation.
1903
Earlier work this paper cites.
Degond P, Mustieles FJ. 1990. A deterministic approximation of diffusion equations using particles. SIAM J. Sci. Comput. 11
1990
Earlier work this paper cites.
Russo G. 1990. Deterministic diffusion of particles. Comm. Pure Appl. Math. 43
1990
Earlier work this paper cites.
McCann R. 1995. Existence and uniqueness of monotone measure-preserving maps. Duke Mathematical Journal 80
1995
Earlier work this paper cites.
Neal RM. 1996. Sampling from multimodal distributions using tempered transitions. Statistics and Computing 6
1996
Earlier work this paper cites.
Burgers G, van Leeuwen PJ, Evensen G. 1998. Analysis scheme in the ensemble Kalman filter. Monthly Weather Review 126
1998
Earlier work this paper cites.
Houtekamer PL, Mitchell HL. 1998. Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev. 126
1998
Earlier work this paper cites.
Pitt MK, Shephard N. 1999. Filtering via simulation: Auxiliary particle filters. Journal of the American Statistical Association 94
1999
Earlier work this paper cites.
van Leeuwen PJ. 2010. Nonlinear data assimilation in Geosciences: An extremely efficient particle filter. Q. J. R. Meteorol. Soc. 136
1999
Earlier work this paper cites.
Doucet A, de Freitas N, Gordon N. 2001. Sequential Monte Carlo methods in practice . Springer
2001
Earlier work this paper cites.
Pham DT. 2001. Stochastic methods for sequential data assimilation in strongly nonlinear systems. Mon. Wea. Rev. 129
2001
Earlier work this paper cites.
Bengtsson T, Snyder C, Nychka D. 2003. Toward a nonlinear ensemble filter for high-dimensional systems. J. Geophys. Res. 108
2003
Earlier work this paper cites.
van Leeuwen PJ. 2003. Nonlinear ensemble data assimilation for the ocean. In: Recent Developments in data assimilation for atmosphere and ocean, ECMWF Seminar 8-12 September 2003, Reading, United Kingdom . pp. 265–286
2003
Earlier work this paper cites.
Robert CP, Cassela G. 2004. Monte Carlo statistical methods . Springer-Verlag
2004
Earlier work this paper cites.
DelMoral P, Doucet A, Jasra A. 2006. Sequential Monte Carlo samplers. J. R. Statist. Soc. B 10.1111/j.1467-9868.2006.00553.x
2006
Earlier work this paper cites.
Vossepoel FC, van Leeuwen PJ. 2006. Parameter estimation using a particle method: Inferring mixing coefficients from sea-level observations. Monthly Weather Rev. 135
2006
Earlier work this paper cites.
Xiong X, Navon IM, Uzunoglu B. 2006. A note on the particle filter with posterior Gaussian resampling. Tellus 58A
2006
Earlier work this paper cites.
Hunt BR, Kostelich EJ, Szunyogh I. 2007. Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter. Physica D 230
2007
Earlier work this paper cites.
Nakano S, Ueno G, Higuchi T. 2007. Merging particle filter for sequential data assimilation. Nonlinear Processes Geophys. 14
2007
Earlier work this paper cites.
Hoteit I, Pham DT, Triantafyllou G, Korres G. 2008. A new approximate solution of the optimal nonlinear filter for data assimilation in meteorology and oceanography. Mon. Wea. Rev. 136
2008
Earlier work this paper cites.
Snyder C, Bengtsson T, Bickel P, Anderson J. 2008. Obstacles to high-dimensional particle filtering. Monthly Weather Review 136
2008
Earlier work this paper cites.
Villani C. 2008. Optimal transport: Old and new . Springer Science & Business Media: New York
2008
Earlier work this paper cites.
van Leeuwen PJ. 2009. Particle filtering in geophysical systems. Mon. Wea. Rev. 137
2009
Earlier work this paper cites.
Chorin AJ, Morzfeld M, Tu X. 2010. Interpolation and iteration for nonlinear filters. Communications in Applied Mathematics and Computational Science 5
2010
Earlier work this paper cites.
Papadakis N, Memin E, Cuzol A, Gengembre N. 2010. Data assimilation with the weighted ensemble kalman filter. Tellus A: Dynamic Meteorology and Oceanography 62
2010
Cited alongside, same era.
Daum F, Huang J. 2011. Particle flow for nonlinear filters. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic . pp. 5920–5923, 10.1109/ICASSP.2011.5947709
2011
Cited alongside, same era.
Lei J, Bickel P. 2011. A moment matching ensemble filter for nonlinear non-Gaussian data assimilation. Mon. Wea. Rev. 139
2011
Cited alongside, same era.
Reich S. 2011. A dynamical systems framework for intermittent data assimilation. BIT Numer Math 51
2011
Cited alongside, same era.
Stordal AS, Karlsen HA, Naevdal G, Skaug HJ, Valles B. 2011. Briding the ensemble Kalman filter and particle filters: the adaptive Gaussian mixture filter. Comput. Geosci. 15
Chustagulprom N, Reich S, Reinhardt M. 2016. A hybrid ensemble transform filter for nonlinear and spatially extended dynamical systems. SIAM/ASA J. Uncertainty Quantification 4
2016
Later among the works it cites.
2016
Later among the works it cites.
Penny S, Miyoshi T. 2016. A local particle filter for high-dimensional geophysical systems. Nonlinear Processes Geophys. 23
2016
Later among the works it cites.
Poterjoy J. 2016. A localized particle filter for high-dimensional nonlinear systems. Monthly Weather Rev. 144
2016
Later among the works it cites.
Poterjoy J, Anderson JL. 2016. Efficient assimilation of simulated observations in a high-dimensional geophysical system using a localized particle filter. Monthly Weather Rev. 144
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2011
Cited alongside, same era.
Moselhy TE, Marzouk Y. 2012. Bayesian inference with optimal maps. J. Comput. Phys. 231
2012
Cited alongside, same era.
Nerger L, Janjić T, Schroeter J, Hiller W. 2012. A unification of ensemble square root filters. Mon. Wea. Rev. 140
2012
Cited alongside, same era.
Reich S. 2012. A Gaussian mixture ensemble transform filter. Q. J. R. Meterolog. Soc. 138
2012
Cited alongside, same era.
Ades M, van Leeuwen PJ. 2013. An exploration of the equivalent weights particle filter. Q. J. R. Meteorol. Soc. 139
2013
Cited alongside, same era.
Briggs J, Dowd M, Meyer R. 2013. Data assimilation for large-scale spatio-temporal systems using a location particle smoother. Environmetrics 24
2013
Cited alongside, same era.
Buehner M, Morneau J, Charette C. 2013. Four-dimensional ensemble-variational data assimilation for global deterministic weather prediction. Nonlinear Processes in Geophysics 20
2013
Cited alongside, same era.
Daum F, Huang J. 2013. Particle flow for nonlinear filters, bayesian decisions and transport. In: Proceedings of the 16th International Conference on Information Fusion, FUSION 2013, Istanbul, Turkey, July 9-12, 2013 . pp. 1072–1079, URL http://ieeexplore.ieee.org/document/6641115/
2013
Cited alongside, same era.
2016
Later among the works it cites.
Schraff C, Reich H, Rhodin A, Schomburg A, Stephan K, Periáñez A, Potthast R. 2016. Kilometre-scale ensemble data assimilation for the COSMO model (kenda). Quarterly J. Roy. Meteorol. Soc. 142
2016
Later among the works it cites.
Tödter J, Kirchgessner P, Nerger L, Ahrens B. 2016. Assessment of a nonlinear ensemble transform filter for high-dimensional data assimilation. Mon. Wea. Rev. 144
2016
Later among the works it cites.
Zhu M, van Leeuwen PJ, Amezcua J. 2016. Implicit equal-weights particle filter. Q. J. R. Meteorol. Soc. 10.1002/qj.2784
2016
Later among the works it cites.
de Wiljes J, Acevedo W, Reich S. 2017. Second-order accurate ensemble transform particle filters. SIAM J. Sci. Comput. 39
2017
Later among the works it cites.
Kirchgessner P, Toedter J, Ahrens B, Nerger L. 2017. The smoother extension of the nonlinear ensemble transform filter. Tellus A 69
2017
Later among the works it cites.
Morzfeld M, Hodyss D, Snyder C. 2017. What the collapse of the ensemble kalman filter tells us about particle filters. Tellus A: Dynamic Meteorology and Oceanography 69
2017
Later among the works it cites.
Robert S, Künsch HR. 2017. Localizing the ensemble transform Kalman particle filter. Tellus A 10.1080/16000870.2017.1282016
2017
Later among the works it cites.
Robert S, Leuenberger D, Künsch HR. 2017. A local ensemble transform Kalman particle filter for convective scale data assimilation. Q. J. R. Meterolog. Soc. 10.1002/qj.3116
2017
Later among the works it cites.
Spantini A, Bigoni D, Marzouk Y. 2017. Inference via low-dimensional couplings. ArXiv:1703.06131
2017
Later among the works it cites.
Evensen G. 2018. Analysis of iterative ensemble smoothers for solving inverse problems. Computational Geosciences 22
2018
Closest in time.
Farchi A, Bocquet M. 2018. Review article: Comparison of local particle filters and new implementations. Nonlin. Processes Geophys. 25
2018
Closest in time.
2018
Closest in time.
2018
Closest in time.
Vetra-Carvalho S, van Leeuwen PJ, Nerger L, Barth A, Altaf MU, Brasseur P, Kirchgessner P, Beckers JM. 2018. State-of-the-art stochastic data assimilation methods for high-dimensional non-gaussian problems. Tellus A: Dynamic Meteorology and Oceanography 70
2018
Closest in time.
Walter A, Potthast R, Rhodin A. 2018. On hybrid particle-filter based ensemble variational data assimilation URL inPreparation
2018
Closest in time.
Potthast R, Walter A, Rhodin A. 2019. A Localized Adaptive Particle Filter within an operational NWP framework. Monthly Wea. Rev. 10.1175/MWR-D-18-0028.1
2019
Closest in time.
Nakamura G, Potthast R. 2015. Inverse modeling . 2053-2563, IOP Publishing, ISBN 978-0-7503-1218-9, 10.1088/978-0-7503-1218-9
2053
Closest in time.
Morzfeld M, Tu X, Atkins E, Chorin AJ. 2012. A random map implementation of implicit filters. Journal of Computational Physics 231
2066
Closest in time.