Results 241 to 250 of about 23,530 (292)

Markov Determinantal Point Process for Dynamic Random Sets

Journal of Time Series Analysis, Volume 47, Issue 4, Page 784-802, July 2026.
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

Robust broadband adaptive beamforming for planar arrays with tunable nulls in high-dynamic scenario. [PDF]

Sci Rep
Hao F, Yu B, Cong Z, Zhang Y, Pan S, Yao Z, Chen Y.   +6 more
europepmc   +1 more source

Wigner Distribution Sets Universal Lower Bound for Quantum Advantage in Gaussian Boson Sampling. [PDF]

Entropy (Basel)
Kocharovsky VV, Kalra K.
europepmc   +1 more source

Estimation of future occurrence of hemoglobin-A1c elevation with and without differential privacy. [PDF]

BMC Med Inform Decis Mak
Alam MA, Hanaoka S, Takenaga T, Yoshikawa T, Abe O.   +4 more
europepmc   +1 more source

Ion-Specific Modulation of the Conformation and Compactness of DNA Oligo-Catenanes. [PDF]

J Phys Chem B
Alexiou TS, Likos CN.
europepmc   +1 more source

Stochastic activity in low-rank recurrent neural networks. [PDF]

PLoS Comput Biol
Mastrogiuseppe F, Carmona J, Machens CK.
europepmc   +1 more source

A Logratio Approach to the Analysis of Autosomal Genotype Frequencies Across Multiple Samples. [PDF]

Mol Ecol Resour
Graffelman J.
europepmc   +1 more source

Eigenvalues and Eigenvectors

, 2023
U ovom diplomskom radu proučavamo svojstvene vrijednosti i svojstvene vektore matrice te njihove primjene. Prvo je poglavlje posvećeno matricama te njihovim svojstvenim vrijednostima.
Abdelwahab Kharab, Ronald B. Guenther
core   +4 more sources

Neural networks based approach for computing eigenvectors and eigenvalues of symmetric matrix

Computers and Mathematics With Applications, 2004
Efficient computation of eigenvectors and eigenvalues of a matrix is an important problem in engineering, especially for computing eigenvectors corresponding to largest or smallest eigenvalues of a matrix.
Yi, Zhang, Fu, Yan, Tang, Hua Jin
exaly   +2 more sources

Distributed Estimation of All the Eigenvalues and Eigenvectors of Matrices Associated With Strongly Connected Digraphs

, 2017
This letter considers the problem of estimating all the eigenvalues and eigenvectors of an irreducible matrix, corresponding to a strongly connected digraph, in the absence of knowledge on the global network topology.
Azwirman Gusrialdi, Zhihua Qu
exaly   +2 more sources