Image deconvolution and reconstruction are inverse problems which are encountered in a
wide array of applications. Due to the ill-posedness of such problems, their resolution …

Variational Bayesian approximations have been widely used in fully Bayesian inference for
approximating an intractable posterior distribution by a separable one. Nevertheless, the …

In this paper, a methodology is investigated for signal recovery in the presence of non-
Gaussian noise. In contrast with regularized minimization approaches often adopted in the …

The noise distribution in the mechanical system is tightly connected to the structure design
and particular operating conditions. The noise source localization can effectively assist with …

Sound source visualization has been widely used in many scenarios such as aerospace,
industrial production, and urban management. Sound source localization technology plays …

This paper considers the linear-Gaussian filtering problem in large-dimensions, a framework
in which the Kalman filter (KF) can be computationally prohibitive. As a remedy, a hybrid …

In this paper, a novel mobile agent-based distributed evidential expectation maximization
(MADEEM) algorithm is presented for sensor networks. The proposed algorithm is used for …

Approximate inference for constructing astronomical catalogs from images Page 1 The Annals
of Applied Statistics 2019, Vol. 13, No. 3, 1884–1926 https://doi.org/10.1214/19-AOAS1258 © …

We present, in this paper, a new unsupervised method for joint image super-resolution and
separation between smooth and point sources. For this purpose, we propose a Bayesian …

In order to reduce the Gaussian noise introduced during image generation, this paper
presents an image denoising algorithm based on variational Bayes (V-Bayes) estimation …