Related papers: Applying the BF method on the DESI evidence for dy…
Dark energy equation of state $w(z)$ parametrizations with two parameters and given monotonicity are generically either convex or concave functions. This makes them suitable for fitting either freezing or thawing quintessence models but not…
When using the finite element method (FEM) in inverse problems, its discretization error can produce parameter estimates that are inaccurate and overconfident. The Bayesian finite element method (BFEM) provides a probabilistic model for the…
We use Bayesian model selection techniques to test extensions of the standard flat LambdaCDM paradigm. Dark-energy and curvature scenarios, and primordial perturbation models are considered. To that end, we calculate the Bayesian evidence…
We perform a detailed analysis of a theoretically motivated dark energy quintessence model which interacts with the dark matter sector of the universe. Utilising the current observational datasets from the Cosmic Microwave Background,…
We consider the problem of learning parameters of latent variable models from mixed (continuous and ordinal) data with missing values. We propose a novel Bayesian Gaussian copula factor (BGCF) approach that is consistent under certain…
Bayesian simulation-based inference (SBI) methods are used in statistical models where simulation is feasible but the likelihood is intractable. Standard SBI methods can perform poorly in cases of model misspecification, and there has been…
We present updated constraints on cosmological parameters in a 12-parameter model, extending the standard six-parameter $\Lambda$CDM by including dynamical dark energy (DE: $w_0$, $w_a$), the sum of neutrino masses ($\sum m_{\nu}$), the…
Understanding of the pathophysiology of obstructive lung disease (OLD) is limited by available methods to examine the relationship between multi-omic molecular phenomena and clinical outcomes. Integrative factorization methods for…
Combined measurements of Baryon Acoustic Oscillations (BAO) from the Dark Energy Spectroscopic Survey (DESI), the Cosmic Microwave Background (CMB) and Type Ia Supernovae (SN Ia), have recently challenged the $\Lambda$-Cold Dark Matter…
We introduce a two-parameter phenomenological extension of the $\Lambda$CDM model in which the equation of state parameter of the ``dust'' fluid becomes different from zero for redshifts below a transition value $z_t$. Using data from DESI…
We investigate a dynamical reconstruction of the dark energy equation of state parameter by assuming that it satisfies a law of motion described by an autonomous second-order differential equation, with the limit of the cosmological…
A fundamental question in cosmology is whether dark energy evolves over time, a topic that has gained prominence since the discovery of cosmic acceleration. Recently, the DESI collaboration has reported increasing evidence for evolving dark…
Even though the Dark Energy Spectroscopic Instrument (DESI) mission does not exclude a dynamical dark energy evolution, the concordance paradigm, i.e., the $\Lambda$CDM model, remains statistically favored, as it depends on the fewest…
In this work, we present a study on cosmological constraints of dark energy (DE) parametrizations after the observations of Dark Energy Spectroscopic Instruments (DESI) for Baryon Acoustic Oscillations (BAO) in 2024, suggesting potential…
The recent results from the first year baryon acoustic oscillations (BAO) data released by the Dark Energy Spectroscopic Instrument (DESI), combined with cosmic microwave background (CMB) and type Ia supernova (SN) data, have shown a…
The is no other model or hypothesis verification tool in Bayesian statistics that is as widely used as the Bayes factor. We focus on generative models that are likelihood-free and, therefore, render the computation of Bayes factors…
In this paper, a Convolution-Based Converter (CBC) is proposed to develop a methodology for removing the strong or fixed priors in estimating the probability distribution of targets based on observations in the stochastic process.…
We explore an interacting dark sector model in trace-free Einstein gravity where dark energy has a constant equation of state, $w=-1$, and the energy-momentum transfer potential is proportional to the cold dark matter density. Compared to…
This paper studies Bayesian variable selection in linear models with general spherically symmetric error distributions. We propose sub-harmonic priors which arise as a class of mixtures of Zellner's g-priors for which the Bayes factors are…
Recent astronomical observations indicate that the Universe is presently almost flat and undergoing a period of accelerated expansion. Basing on Einstein's general relativity all these observations can be explained by the hypothesis of a…