Related papers: Gaussian mixture model and population synthesis of…
The Collective Graphical Model (CGM) models a population of independent and identically distributed individuals when only collective statistics (i.e., counts of individuals) are observed. Exact inference in CGMs is intractable, and previous…
The Fermi Gamma-Ray Space Telescope has discovered many gamma-ray pulsars, both as radio-loud objects and radio-quiet or radio-weak pulsars that have been identified through blind period searches. The latter presumably have gamma-ray beams…
The EGRET telescope on the Compton Gamma-Ray Observatory detected over 200 sources and the majority of these are still unidentified. At least three subpopulations of EGRET sources have been associated with the Galaxy: bright sources lying…
Determining the number of clusters is a fundamental issue in data clustering. Several algorithms have been proposed, including centroid-based algorithms using the Euclidean distance and model-based algorithms using a mixture of probability…
The Gaussian mixture model (GMM) provides a simple yet principled framework for clustering, with properties suitable for statistical inference. In this paper, we propose a new model-based clustering algorithm, called EGMM (evidential GMM),…
Recursive estimation of nonlinear dynamical systems is an important problem that arises in several engineering applications. Consistent and accurate propagation of uncertainties is important to ensuring good estimation performance. It is…
In this paper, the third in a series illustrating the power of generalized linear models (GLMs) for the astronomical community, we elucidate the potential of the class of GLMs which handles count data. The size of a galaxy's globular…
High sensitivity searches of globular clusters (GC) for radio pulsars by improved pulsar search algorithms and sustained pulsar timing observations have so far yielded some 140 pulsars in more than two dozen GCs. The observed distribution…
Cluster analysis of biological samples using gene expression measurements is a common task which aids the discovery of heterogeneous biological sub-populations having distinct mRNA profiles. Several model-based clustering algorithms have…
The computation of theoretical pulsar populations has been a major component of pulsar studies since the 1970s. However, the majority of pulsar population synthesis has only regarded isolated pulsar evolution. Those that have examined…
Copulas provide a modular parameterization of multivariate distributions that decouples the modeling of marginals from the dependencies between them. Gaussian Mixture Copula Model (GMCM) is a highly flexible copula that can model many kinds…
We propose a projection pursuit (PP) algorithm based on Gaussian mixture models (GMMs). The negentropy obtained from a multivariate density estimated by GMMs is adopted as the PP index to be maximised. For a fixed dimension of the…
Over a hundred millisecond radio pulsars (MSPs) have been observed in globular clusters (GCs), motivating theoretical studies of the formation and evolution of these sources through stellar evolution coupled to stellar dynamics. Here we…
Millisecond pulsars (MSPs) are abundant in globular clusters (GCs), which offer favorable environments for their creation. While the advent of recent, powerful facilities led to a rapid increase in MSP discoveries in GCs through pulsation…
In this letter, we propose a Gaussian mixture model (GMM)-based channel estimator which is learned on imperfect training data, i.e., the training data are solely comprised of noisy and sparsely allocated pilot observations. In a practical…
We compare population synthesis results for inner and outer magnetosphere emission models with the various characteristics measured in the first LAT pulsar catalogue for both the radio-loud and radio-weak or radio-quiet gamma-ray pulsars.…
Since the discovery of Quasi-stellar Objects (QSOs), also known as quasars, they have been traditionally subdivided as radio-loud and radio-quiet sources. Whether such division is a misleading effect from a highly heterogeneous single…
A novel Gaussian mixture model (GMM) aided sparse Bayesian learning (SBL) framework is proposed for channel state information (CSI) estimation in orthogonal time-frequency space (OTFS) modulated systems. The key attribute of the proposed…
Inspired by increase of population of $\gamma$-ray emitting pulsars by the $Fermi$ telescope, we perform a population study for $\gamma$-ray emitting canonical pulsars. We use a Monte-Carlo technique to simulate the Galactic population of…
We develop here a semiparametric Gaussian mixture model (SGMM) for unsupervised learning with valuable spatial information taken into consideration. Specifically, we assume for each instance a random location. Then, conditional on this…