Related papers: Reply to "Comment on 'Ensemble Kalman filter with …
The ensemble Kalman filter (EnKF) has become a standard methodology for state estimation in high-dimensional systems, yet its various stochastic and deterministic formulations often appear conceptually disconnected. In this paper, a unified…
We introduce a new multilevel ensemble Kalman filter method (MLEnKF) which consists of a hierarchy of independent samples of ensemble Kalman filters (EnKF). This new MLEnKF method is fundamentally different from the preexisting method…
Comment on "Gapless Spin-1 Neutral Collective Mode Branch for Graphite" by G. Baskaran and S.A. Jafari [cond-mat/0110022; Physical Review Letters, 89, 016402 (2002)].
This is a reply to the comment by A. W. Sandvik (cond-mat/0010433) on our paper Phys. Rev. Lett. 84, 4204 (2000). We show that his data do not conflict with our data nor with our conclusions.
Ensemble filters implement sequential Bayesian estimation by representing the probability distribution by an ensemble mean and covariance. Unbiased square root ensemble filters use deterministic algorithms to produce an analysis (posterior)…
The unscented transformation (UT) is an efficient method to solve the state estimation problem for a non-linear dynamic system, utilizing a derivative-free higher-order approximation by approximating a Gaussian distribution rather than…
We reply to a comment by Averin and Korotkov http://uk.arxiv.org/abs/cond-mat/0404549 on Stace and Barrett, PRL 92, 136802 (2004) http://link.aps.org/abstract/PRL/v92/e136802, showing that their specific criticisms are unfounded, and…
The Comment by Holas et al. [A. Holas, M. Cinal, and N. H. March, Phys. Rev. A 78, 016501 (2008)] on our recent paper [J. Schirmer and A. Dreuw, Phys. Rev. A 75, 022513 (2007)]. is an appropriate and valuable contribution. As a small…
This study considers the data assimilation problem in coupled systems, which consists of two components (sub-systems) interacting with each other through certain coupling terms. A straightforward way to tackle the assimilation problem in…
The Gaussian process state-space models (GPSSMs) represent a versatile class of data-driven nonlinear dynamical system models. However, the presence of numerous latent variables in GPSSM incurs unresolved issues for existing variational…
We propose a method for inference on moderately high-dimensional, nonlinear, non-Gaussian, partially observed Markov process models for which the transition density is not analytically tractable. Markov processes with intractable transition…
This is a Reply on the proceeding comment on our paper titled "Classical Simulations Including Electron Correlations for Sequential Double Ionization".
Rejoinder to ``Equi-energy sampler with applications in statistical inference and statistical mechanics'' by Kou, Zhou and Wong [math.ST/0507080]
Discussion of ``EQUI-energy sampler'' by Kou, Zhou and Wong [math.ST/0507080]
Discussion of ``EQUI-energy sampler'' by Kou, Zhou and Wong [math.ST/0507080]
We present a practical implementation of the ensemble Kalman (EnKF) filter based on an iterative Sherman-Morrison formula. The new direct method exploits the special structure of the ensemble-estimated error covariance matrices in order to…
This is a reply to the comment by J. L. Alonso et al. (arXiv:1302.6146; to appear in J. Chem. Phys) on our paper A. Abedi, N. T. Maitra, and E. K. U. Gross, J. Chem. Phys. 137, 22A530 (2012) [arXiv: 1208.4388]
The ensemble Kalman filter (EnKF) is widely used for nonlinear and high-dimensional state estimation because it replaces complex covariance propagation with simple ensemble statistics. However, conventional EnKF implementations can become…
I reply to a Comment by Q. Wang and W.G. Unruh regarding my paper "Hiding the Cosmological Constant" [Phys. Rev. Lett. 123, 131302].
We are pleased to see that Jeckelmann has made many changes to the original version of his comment on our paper as a result of our response. Here is a copy of this powerful response that reveals problems in his previous results. However,…