Related papers: Gaussian mixture model and population synthesis of…
We discuss the diffuse emission of gamma rays and neutrinos from galaxy clusters in the viable models for structure formation in the universe. We use a self-consistent picture for cluster formation and evolution starting from a primordial…
The classical Gaussian mixture model assumes homogeneity within clusters, an assumption that often fails in real-world data where observations naturally exhibit varying scales or intensities. To address this, we introduce the…
Context: Globular clusters (GCs) host multiple populations characterised by abundance variations in a number of light elements. In many cases, these populations also show spatial and/or kinematic differences, which vary in strength from…
Pulsars orbiting the Galactic center black hole, Sgr A*, would be potential probes of its mass, distance and spin, and may even be used to test general relativity. Despite predictions of large populations of both ordinary and millisecond…
Clustering and estimating cluster means are core problems in statistics and machine learning, with k-means and Expectation Maximization (EM) being two widely used algorithms. In this work, we provide a theoretical explanation for the…
Modeling of frequency-dependent effects, contributed by the turbulence in the free electron density of interstellar plasma, is required to enable the detection of the expected imprints from the stochastic gravitational-wave (GW) background…
Gamma-ray observations have shown pulsars to be efficient converters of rotational energy into GeV photons and it is of wide-ranging interest to determine their contribution to the gamma-ray background. We arrive at flux predictions from…
In an earlier paper (Ahuja, et al, 2005), based on simultaneous multi-frequency observations with the Giant Metrewave Radio Telescope (GMRT), we reported the variation of pulsar dispersion measures (DMs) with frequency. A few different…
Gravitational lensing magnification bias is a valuable tool for studying mass density profiles, with submillimetre galaxies (SMGs) serving as ideal background sources. The satellite distribution in galaxy clusters also provides insights…
Observations of millisecond pulsars (MSPs) at low radio frequencies play an important role in understanding the Galactic pulsar population and characterising both their emission properties and the effects of the ionised interstellar medium…
Learning a Gaussian mixture model (GMM) is a fundamental problem in machine learning, learning theory, and statistics. One notion of learning a GMM is proper learning: here, the goal is to find a mixture of $k$ Gaussians $\mathcal{M}$ that…
Currently three isolated radio pulsars and one binary radio pulsar with no evidence of any previous recycling are known in 97 surveyed Galactic globular clusters. As pointed out by Lyne et al., the presence of these pulsars cannot be…
Conditional density estimation is complicated by multimodality, heteroscedasticity, and strong non-Gaussianity. Gaussian processes (GPs) provide a principled nonparametric framework with calibrated uncertainty, but standard GP regression is…
We simulate the characteristics of the Galactic population of radio and $\gamma$-ray pulsars using Monte Carlo techniques. At birth, neutron stars are spatially distributed in the Galactic disk, with supernova-kick velocities, and randomly…
Clustering task of mixed data is a challenging problem. In a probabilistic framework, the main difficulty is due to a shortage of conventional distributions for such data. In this paper, we propose to achieve the mixed data clustering with…
Diffusion models have become a standard approach for generative modeling in continuous domains, yet their application to discrete data remains challenging. We investigate why Gaussian diffusion models with the DDPM solver struggle to sample…
We investigate the landscape of the negative log-likelihood function of Gaussian Mixture Models (GMMs) with a general number of components in the population limit. As the objective function is non-convex, there can be multiple local minima…
The finding of multiple stellar populations (MP), defined by patterns in the stellar element abundances, is nowadays considered a distinctive feature of globular clusters. However, while data availability and quality improved in last…
Non-Gaussian mixture models are gaining increasing attention for mixture model-based clustering particularly when dealing with data that exhibit features such as skewness and heavy tails. Here, such a mixture distribution is presented,…
We present a comparative study of the Gaussian mixture model (GMM) and the Deep Autoencoder Gaussian Mixture Model (DAGMM) for estimating satellite quantum channel capacity, considering hybrid quantum noise (HQN) and transmission…