Related papers: Reconstructing AGN X-ray spectral parameter distri…
We present here RadioSED, a Bayesian inference framework tailored to modelling and classifying broadband radio spectral energy distributions (SEDs) using only data from publicly-released, large-area surveys. We outline the functionality of…
Approximate Bayesian Computation (ABC) methods are commonly used to approximate posterior distributions in models with unknown or computationally intractable likelihoods. Classical ABC methods are based on nearest neighbor type algorithms…
When modeling a probability distribution with a Bayesian network, we are faced with the problem of how to handle continuous variables. Most previous work has either solved the problem by discretizing, or assumed that the data are generated…
Combining multiple events into population analyses is a cornerstone of gravitational-wave astronomy. A critical component of such studies is the assumed population model, which can range from astrophysically motivated functional forms to…
Monte Carlo methods are often necessary for the implementation of optimal Bayesian estimators. A fundamental technique that can be used to generate samples from virtually any target probability distribution is the so-called rejection…
The "Cosmic Evolution Survey" (COSMOS) enables the study of the Spectral Energy Distributions (SEDs) of Active Galactic Nuclei (AGN) because of the deep coverage and rich sampling of frequencies from X-ray to radio. Here we present a SED…
We present a new Bayesian algorithm making use of Markov Chain Monte Carlo sampling that allows us to simultaneously estimate the unknown continuum level of each quasar in an ensemble of high-resolution spectra, as well as their common…
In image reconstruction, an accurate quantification of uncertainty is of great importance for informed decision making. Here, the Bayesian approach to inverse problems can be used: the image is represented through a random function that…
We present a novel Bayesian method for the joint reconstruction of cosmological matter density fields, peculiar velocities and power-spectra in the quasi-nonlinear regime. We study its applicability to the Ly-alpha forest based on multiple…
Background: Continuous traits evolution of a group of taxa that are correlated through a phylogenetic tree is commonly modelled using parametric stochastic differential equations to represent deterministic change of trait through time,…
We compiled a sample of 95 AGNs serendipitously detected in the 3-20 keV band at Galactic latitude |b|>10 during the RXTE slew survey (XSS, Revnivtsev et al.), and utilize it to study the statistical properties of the local population of…
This paper investigates what constraints can be placed on the fraction of Compton-thick (CT) AGN in the Universe from the modeling of the spectrum of the diffuse X-ray background (XRB). We present a model for the synthesis of the XRB that…
Bayesian methods are a popular choice for statistical inference in small-data regimes due to the regularization effect induced by the prior. In the context of density estimation, the standard nonparametric Bayesian approach is to target the…
Changes in population size influence genetic diversity of the population and, as a result, leave a signature of these changes in individual genomes in the population. We are interested in the inverse problem of reconstructing past…
The Two Micron All Sky Survey (2MASS) is finding previously unidentified, luminous red active galactic nuclei (AGN). This new sample has a space density similar to, or greater than, previously known AGN, suggesting that a large fraction of…
We study the comoving space density of X-ray-selected luminous active galactic nuclei (AGNs) and the obscured AGN fraction at high redshifts ($3 < z < 5$) in the Subaru/{\it XMM-Newton} Deep Survey (SXDS) field. From an X-ray source catalog…
The assembly and co-evolution of supermassive black holes (SMBH) and their host galaxy stellar population is a key open questions in galaxy evolution. Stellar mass ($M_\star$) and star formation rate (SFR), are inferred by modeling the…
We present a compression algorithm for parton densities using synthetic replicas generated from the training of a Generative Adversarial Network (GAN). The generated replicas are used to further enhance the statistics of a given Monte Carlo…
To infer the parameters of mechanistic models with intractable likelihoods, techniques such as approximate Bayesian computation (ABC) are increasingly being adopted. One of the main disadvantages of ABC in practical situations, however, is…
Active galactic nuclei (AGN) are typically identified through their distinctive X-ray or radio emissions, mid-infrared (MIR) colors, or emission lines. However, each method captures different subsets of AGN due to signal-to-noise (SNR)…