Abstract: In this work, a kernel-based Ensemble Gaussian Mixture Probability Hypothesis Density (EnGM-PHD) filter is presented for multi-target filtering applications. The EnGMPHD filter combines the ...

Kernel density estimation (KDE) and nonparametric methods form a cornerstone of contemporary statistical analysis. Unlike parametric approaches that assume a specific functional form for the ...

Gordon Lee et al introduce a data-driven and model-agnostic approach for computing conditional expectations. The new method combines classical techniques with machine learning methods, in particular ...

This is a preview. Log in through your library . Abstract Sequential Monte Cario (SMC) methods, also known as particle filters, are simulation-based recursive algorithms for the approximation of the a ...