Related papers: Approximate Bayesian Computation Applied to the Di…

ABC (approximate Bayesian computation) is a general approach for dealing with models with an intractable likelihood. In this work, we derive ABC algorithms based on QMC (quasi- Monte Carlo) sequences. We show that the resulting ABC…

We present an analysis of the radial angular profile of the galacto-isotropic (GI) $\gamma$-ray flux--the statistically uniform flux in circular annuli about the Galactic center. Two different approaches are used to measure the GI flux…

We explore the possibility that the diffuse gamma-ray background radiation (GBR) at high galactic latitudes could be dominated by inverse Compton scattering of cosmic ray (CR) electrons on the cosmic microwave background radiation and on…

Gibbs random fields (GRF) are polymorphous statistical models that can be used to analyse different types of dependence, in particular for spatially correlated data. However, when those models are faced with the challenge of selecting a…

Approximate Bayesian computation (ABC) is a simulation-based likelihood-free method applicable to both model selection and parameter estimation. ABC parameter estimation requires the ability to forward simulate datasets from a candidate…

Approximate Bayes Computations (ABC) are used for parameter inference when the likelihood function of the model is expensive to evaluate but relatively cheap to sample from. In particle ABC, an ensemble of particles in the product space of…

The power of fuzz testing lies in its random, often brute-force, generation and execution of inputs to trigger unexpected behaviors and vulnerabilities in software applications. However, given the reality of infinite possible input…

There is an increasing amount of literature focused on Bayesian computational methods to address problems with intractable likelihood. One approach is a set of algorithms known as Approximate Bayesian Computational (ABC) methods. One of the…

In this work, we revisit the all-sky Galactic diffuse $\gamma$-ray emission taking into account the new measurements of cosmic ray electron/positron spectrum by PAMELA, ATIC and Fermi, which show excesses of cosmic electrons/positrons…

While dark matter (DM) is the key ingredient for a successful theory of structure formation, its microscopic nature remains elusive. Indirect detection may provide a powerful test for some strongly motivated DM particle models.…

Approximate Bayesian Computation (ABC) methods rely on asymptotic arguments, implying that parameter inference can be systematically biased even when sufficient statistics are available. We propose to construct the ABC accept/reject step…

We implemented a novel technique to perform the collective spectral analysis of sets of multiple gamma-ray point sources using the data collected by the Large Area Telescope onboard the Fermi satellite. The energy spectra of the sources are…

We examine the constraints on the luminosity-dependent density evolution model for the evolution of blazars given the observed spectrum of the diffuse gamma-ray background (DGRB), blazar source-count distribution, and the blazar spectral…

We construct empirical models of the diffuse gamma-ray background toward the Galactic Center. Including all known point sources and a template of emission associated with interactions of cosmic rays with molecular gas, we show that the…

Gamma-ray bursts (GRBs) are believed to be powered by ultrarelativistic jets. If these jets encounter and accelerate excess electrons and positrons produced by particle dark matter (DM) annihilation, the observed electromagnetic radiation…

Approximate Bayesian computation (ABC) refers to a family of inference methods used in the Bayesian analysis of complex models where evaluation of the likelihood is difficult. Conventional ABC methods often suffer from the curse of…

Likelihood-free inference provides a rigorous approach to preform Bayesian analysis using forward simulations only. The main advantage of likelihood-free methods is its ability to account for complex physical processes and observational…

The cosmic infrared background (CIB) contains emissions accumulated over the entire history of the Universe, including from objects inaccessible to individual telescopic studies. The near-IR (~1-10 mic) part of the CIB, and its…

Approximate Bayesian Computation (ABC) is typically used when the likelihood is either unavailable or intractable but where data can be simulated under different parameter settings using a forward model. Despite the recent interest in ABC,…

We present a new formalism designed to discover dark matter annihilation occurring in the Milky Way's dwarf galaxies. The statistical framework extracts all available information in the data by simultaneously combining observations of all…