… We combine diffusion maps, a manifold learning technique, with a linear Kalman filter and
with concepts from Koopman operator theory. More concretely, using diffusion maps, we …

… to the two diffusion tensor and analytical Q-ball models of interest. Then, we present the
Kalman filtering framework and we focus on the optimization of the diffusion orientation sets in …

… Kalman filter; (ii) particle flow algorithms for nonlinear filtering; and (iii… Ensemble Kalman
filter: The EnKF algorithm was first … Compared to the Kalman filter, the main utility of EnKF is that …

… Therefore, we want to adjust the information weight of sensors by modifying the diffusion
matrix C; that is our motivation behind putting forward the deep diffusion Kalman filter (DDKF). …

… This progress poses significant challenges to classical parametric techniques, such as
the seminal Kalman filter (KF) [1], since their prototypical linear and Gaussian models do not …

… OBJECTIVE In this study the authors investigated the clinical reliability of diffusion weighted
imaging maximum a posteriori probability (DWI-MAP) analysis with Kalman filter prediction …

… The Kalman filter works to extract … Kalman filter, an adaptive filter technique, has been
applied to MRI data, allowing an optimal estimation of permeability coefficient. The Kalman filter is …

… Then we focus on the optimization of the diffusion gradient orientation set in section 2.3…
diffusion Kalman filter in order to process incremental connectivity maps during ongoing diffusion …

… approximations to the sequential Bayesian filtering problem in the nonlinear setting. … filter
and a recently proposed approximation of the associated gain function based on diffusion maps…

… Adaptive estimation of optimal combination weights for partialdiffusion Kalman filtering
together with its mean convergence and stability analysis is proposed here. The simulations …