Results 221 to 230 of about 174,528 (270)

Macroscopic Thermalization for Highly Degenerate Hamiltonians After Slight Perturbation. [PDF]

J Stat Phys
Roos B, Sugimoto S, Teufel S, Tumulka R, Vogel C.   +4 more
europepmc   +1 more source

Variance Matrix Priors for Dirichlet Process Mixture Models With Gaussian Kernels

International Statistical Review, EarlyView.
Summary Bayesian mixture modelling is widely used for density estimation and clustering. The Dirichlet process mixture model (DPMM) is the most popular Bayesian non‐parametric mixture modelling approach. In this manuscript, we study the choice of prior for the variance or precision matrix when Gaussian kernels are adopted.
Wei Jing, Michail Papathomas, Silvia Liverani   +2 more
wiley   +1 more source

Multi-task genomic prediction using gated residual variable selection neural networks. [PDF]

BMC Bioinformatics
Fan Y, Waldmann P.
europepmc   +1 more source

Generalizing Determinacy under Monetary and Fiscal Policy Switches: The Case of the Zero Lower Bound

Journal of Money, Credit and Banking, EarlyView.
Abstract In a fixed‐regime context, it has been established since the work of Leeper (1991) that a determinate and unique equilibrium can be achieved under both monetary dominance (characterized by an active monetary policy and a passive fiscal policy) and fiscal dominance (characterized by an active fiscal policy and a passive monetary policy) regimes
SEONGHOON CHO, ANTONIO MORENO
wiley   +1 more source

The eigenvalues and eigenvectors of finite, low rank perturbations of large random matrices

, 2011
Florent Benaych-Georges, Raj Rao Nadakuditi   +1 more
openalex   +1 more source

Unveiling multiscale spatiotemporal dynamics of volatility in high-frequency financial markets. [PDF]

PLoS One
Ouyang F, Peng W, Chen T.
europepmc   +1 more source

Industry Exposure to Artificial Intelligence, Board Network Heterogeneity, and Firm Idiosyncratic Risk

Journal of Management Studies, EarlyView.
Abstract Despite the growing impact of artificial intelligence (AI) in business, there is little research examining its effects on firm idiosyncratic risk (IR). This is an important issue for boards: as key conduits of firm–environment information flows via board interlock networks, traditional risk oversight functions are being increasingly augmented ...
Kerry Hudson, Robert E. Morgan
wiley   +1 more source

Markov Determinantal Point Process for Dynamic Random Sets

Journal of Time Series Analysis, EarlyView.
ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley   +1 more source

Eigenvalues and Low Energy Eigenvectors of Quantum Many-Body Systems

, 2012
Ramis Movassagh
openalex   +2 more sources

A Complex Structure for Two-Typed Tangent Spaces. [PDF]

Entropy (Basel)
Naudts J.
europepmc   +1 more source