9 papers
Unbiased estimation of squared concentration in the Fisher-von Mises-Langevin distribution and the impossibility of unbiased concentration
Zain Jabbar, Yuqin Jiang, Andrey A. Popov
The estimation of concentration parameter in Fisher-von Mises-Langevin distribution is the directional statistics analogue of the estimation of the precision matrix for the Gaussia…
Pose Tracking with a Foundation Pose Model and an Ensemble Directional Kalman Filter
Tianlu Lu, Asif Sijan, Thomas Noh +2
This paper introduces the ensemble directional Kalman filter (EnDKF), an ensemble-based Kalman filtering approach for pose tracking that jointly estimates an object's position and…
Learning Discriminators for Resampling in the Ensemble Gaussian Mixture Filter through a Normalizing Flow Approach
Zain Jabbar, Andrey A. Popov
The ensemble Gaussian mixture filter (EnGMF) is a powerful, convergent particle filter capable of medium-to-high dimensional non-linear filtering. The EnGMF relies on a resampling…
Learning to Trust AI and Data-driven models in Data Assimilation through a Multifidelity Ensemble Gaussian Mixture Filter Framework
Andrey A. Popov
AI and data-driven models have large potential for data assimilation applications by creating fast and accurate forecasts. Their tendency to produce spurious inaccurate, nonphysica…
A divide and conquer strategy for multinomial particle filter resampling
Andrey A. Popov
This work provides a new multinomial resampling procedure for particle filter resampling, focused on the case where the number of samples required is less than or equal to the size…
Deterministic Optimal Transport-based Gaussian Mixture Particle Filtering for Verifiable Applications
Andrey A Popov, Renato Zanetti
Mixture-model particle filters such as the ensemble Gaussian mixture filter require a resampling procedure in order to converge to exact Bayesian inference. Canonically, stochastic…