Bayesian filtering provides a principled framework for estimating the hidden dynamics of a system from noisy or incomplete observations. At its core lies the recursive computation of a posterior ...

The increasing interest in Bayesian group sequential design is due to its potential to reinforce efficiency in clinical trials, shorten drug development time, and enhance the accuracy of statistical ...

A comparative implementation of real-time mouse cursor tracking using two state estimation approaches: traditional Kalman Filter and GTSAM Factor Graphs. This repository demonstrates the fundamental ...

Abstract: For multi-radar target tracking, an adaptive deep sequential fusion with sequential filtering method (ADSF) is proposed in this paper. In the proposed method, the efficient filtering ...