Related papers: Reply to "Comment on 'Ensemble Kalman filter with …
In this paper, stochastic optimal control problems in continuous time and space are considered. In recent years, such problems have received renewed attention from the lens of reinforcement learning (RL) which is also one of our motivation.…
Comments on paper 'Thermometer Effect: Origin of the Mixed Alkali Effect in Glass Relaxation' by Y.Yu et al. published by Physical Review Letters
A combinatorial characterization of measurable filters on a countable set is found. We apply it to the problem of measurability of the intersection of nonmeasurable filters.
This is a reply to a comment on the paper arXiv:1204.2075 "Are stress-free membranes really tensionless ?" (EPL 95,28008 (2011)).
Ensemble data assimilation methods such as the Ensemble Kalman Filter (EnKF) are a key component of probabilistic weather forecasting. They represent the uncertainty in the initial conditions by an ensemble which incorporates information…
We reply to the comment by Ying Zhang and S. Das Sarma on our PRL 94, 226405 (2005).
This is a reply to a Comment on 'A test-tube model for rainfall', {\it Europhys. Lett.}, {\bf 106}, 40001, (2014).
We respond to the recent comment [arXiv:1105.1593] on our Letter [G. G. Plunk and T. Tatsuno, Phys. Rev. Lett. 106, 165003 (2011)]. The comment claims that our argument for spectral transfer direction is incomplete. The comment gives an…
Data assimilation provides algorithms for widespread applications in various fields. It is of practical use to deal with a large amount of information in the complex system that is hard to estimate. Weather forecasting is one of the…
Based on the recently developed theory of Unscented Kalman Inversion in computational mathematics, we proposed a Bayesian joint inversion framework, i.e., Multi-task Unscented Kalman Inversion (MTUKI), and apply it to the joint inversion of…
This unpublished paper is a copy (completed by a development of section 5 and by minor corrections) of the article with the same title published in: Complex Analysis and Digital Geometry, Proceedings from the Kiselmanfest, 2006, Acta…
This is a reply to the comment to a letter by D. Mandal, K. Klymko and M. R. DeWeese published as Phys. Rev. Lett. 119, 258001 (2017).
The ensemble Kalman filter (EnKF) is a data assimilation technique that uses an ensemble of models, updated with data, to track the time evolution of a usually non-linear system. It does so by using an empirical approximation to the…
This is a reply to a comment on our work recently posted in arXiv. To our knowledge, this comment has not been published anywhere else. We show that the points raised in the comment are invalid
This is a Comment to the recent review by L. Glozman, hep-ph/0701081
This is a Reply to the Comment (cond-mat/9812331) by Kravchenko et al. on our earlier work (cond-mat/9812216).
This paper investigates an approximation scheme of the optimal nonlinear Bayesian filter based on the Gaussian mixture representation of the state probability distribution function. The resulting filter is similar to the particle filter,…
In a recent Comment, Kolf et al. (cond-mat/0503669) state that our analysis of the Fano resonance for Anderson impurity systems [Luo et al., Phys. Rev. Lett 92, 256602 (2004)] is incorrect. Here we want to point out that their comments are…
Orientation estimation for 3D objects is a common problem that is usually tackled with traditional nonlinear filtering techniques such as the extended Kalman filter (EKF) or the unscented Kalman filter (UKF). Most of these techniques assume…
Achieving highly accurate dynamic or simulator models that are close to the real robot can facilitate model-based controls (e.g., model predictive control or linear-quadradic regulators), model-based trajectory planning (e.g., trajectory…