Many experimental proposals for noisy intermediate scale quantum devices involve training
a parameterized quantum circuit with a classical optimization loop. Such hybrid quantum …

This is part II of a review relating to the three classes of random non-Hermitian Gaussian
matrices introduced by Ginibre in 1965. While part I restricted attention to the GinUE (Ginibre …

Recent works on Bayesian neural networks (BNNs) have highlighted the need to better
understand the implications of using Gaussian priors in combination with the compositional …

We consider increasingly complex models of matrix denoising and dictionary learning in the
Bayes-optimal setting, in the challenging regime where the matrices to infer have a rank …

Recently, the multiple-input–multiple-output (MIMO) nonorthogonal multiple-access (NOMA)
transmission, denoted as MIMO-NOMA, has been widely applied for Internet of Things (IoT) …

Random matrix theory is a useful tool in the study of the physics of multiple scattering
systems, often striking a balance between computation speed and physical rigour …

We show how the replica method can be used to compute the asymptotic eigenvalue
spectrum of a real Wishart product matrix. For unstructured factors, this provides a compact …

Consider the following asynchronous, opportunistic communication model over a graph $ G
$: in each round, one edge is activated uniformly and independently at random and (only) its …

We establish a few properties of eigenvalues and eigenvectors of the quaternionic Ginibre
ensemble (QGE), analogous to what is known in the complex Ginibre case (see [7, 11, 14]) …

We present a null model for single-and multi-layered complex systems constructed using
homogeneous and isotropic random Gaussian maps. By means of a Kac–Rice formalism …