Related papers: Gaussian mixture model and population synthesis of…
Creating low dimensional representations of a high dimensional data set is an important component in many machine learning applications. How to cluster data using their low dimensional embedded space is still a challenging problem in…
We present the Gaussian process dynamical mixture model (GPDMM) and show its utility in single-example learning of human motion data. The Gaussian process dynamical model (GPDM) is a form of the Gaussian process latent variable model…
We have used millisecond pulsars (MSPs) from the southern High Time Resolution Universe (HTRU) intermediate latitude survey area to simulate the distribution and total population of MSPs in the Galaxy. Our model makes use of the scale…
Gaussian Mixture Models are one of the most studied and mature models in unsupervised learning. However, outliers are often present in the data and could influence the cluster estimation. In this paper, we study a new model that assumes…
Binary population synthesis simulations allow detailed modelling of gravitational-wave sources from a variety of formation channels. These population models can be compared to the observed catalogue of merging binaries to infer the…
A longstanding problem in machine learning is to find unsupervised methods that can learn the statistical structure of high dimensional signals. In recent years, GANs have gained much attention as a possible solution to the problem, and in…
Conditional correlation networks, within Gaussian Graphical Models (GGM), are widely used to describe the direct interactions between the components of a random vector. In the case of an unlabelled Heterogeneous population, Expectation…
In this paper, we describe a novel experiment for the accurate estimation of pulsar dispersion measures using the Giant Metre-wave Radio Telescope. This experiment was carried out for a sample of twelve pulsars, over a period of more than…
Because of its mathematical tractability, the Gaussian mixture model holds a special place in the literature for clustering and classification. For all its benefits, however, the Gaussian mixture model poses problems when the data is skewed…
Astronomical data often suffer from noise and incompleteness. We extend the common mixtures-of-Gaussians density estimation approach to account for situations with a known sample incompleteness by simultaneous imputation from the current…
The number of millisecond pulsars (MSPs) observed in Milky Way globular clusters has increased explosively in recent years, but the underlying population is still uncertain due to observational biases. We use state-of-the-art $N$-body…
Pulsars are rapidly rotating neutron stars that emit radiation across the electromagnetic spectrum, from radio to gamma-rays. We use the rapid binary population synthesis suite COMPAS to model the Galactic population of canonical pulsars.…
We present a Bayesian inference approach to estimating the cumulative mass profile and mean squared velocity profile of a globular cluster given the spatial and kinematic information of its stars. Mock globular clusters with a range of…
We propose an Gaussian Mixture Model (GMM) learning algorithm, based on our previous work of GMM expansion idea. The new algorithm brings more robustness and simplicity than classic Expectation Maximization (EM) algorithm. It also improves…
Mixture models are a natural choice in many applications, but it can be difficult to place an a priori upper bound on the number of components. To circumvent this, investigators are turning increasingly to Dirichlet process mixture models…
Forecasting on sparse multivariate time series (MTS) aims to model the predictors of future values of time series given their incomplete past, which is important for many emerging applications. However, most existing methods process MTS's…
Studying the effects of air-pollution on health is a key area in environmental epidemiology. An accurate estimation of air-pollution effects requires spatio-temporally resolved datasets of air-pollution, especially, Fine Particulate Matter…
In this paper, I review some of the basic properties of the pulsar population in globular clusters (GCs) and compare it with the the Galactic disk population. The neutron stars (NSs) in GCs were likely formed - and appear to continue…
We calculate the joint period-spindown (P-Pdot) distributions of millisecond radio pulsars (MSRP) for the standard evolutionary model in order to test whether the observed MSRPs are the unequivocal descendants of millisecond X-ray pulsars…
This thesis work is focused on the study of millisecond pulsars in globular cluster by using multi-wavelength observations obtained with radio and optical telescopes. Radio observations have been used to search for and timing the pulsars.…