Results 201 to 210 of about 411,141 (342)
Exploring Causal Learning Through Graph Neural Networks: An In‐Depth Review
WIREs Data Mining and Knowledge Discovery, Volume 15, Issue 2, June 2025.Graphical abstract of the survey with a taxonomical approach to causal learning with graph neural networks. ABSTRACT In machine learning, exploring data correlations to predict outcomes is a fundamental task. Recognizing causal relationships embedded within data is pivotal for a comprehensive understanding of system dynamics, the significance of which ...
Simi Job +6 more
wiley +1 more source
On a structure formula for classical q-orthogonal polynomials
, 2001 Wolfram Koepf, Dieter Schmersau
openalex +1 more source
Geochemistry, Geophysics, Geosystems, Volume 26, Issue 6, June 2025.Abstract Simulating present‐day solid Earth deformation and volatile cycling requires integrating diverse geophysical data sets and advanced numerical techniques to model complex multiphysics processes at high resolutions. Subduction zone modeling is particularly challenging due to the large geographic extent, localized deformation zones, and the ...
D. Douglas +5 more
wiley +1 more source
Classical Orthogonal Polynomials of a Discrete Variable
, 1991 A. Nikiforov +2 more
semanticscholar +1 more source
Time‐Series Factor Modeling and Selection
Journal of Financial Research, Volume 48, Issue 2, Page 839-875, Summer 2025.Abstract The article proposes a statistical time‐series factor model that incorporates deterministic orthogonal trend polynomials. Such polynomials allow capturing variation in returns without initially identifying a set of robust time‐series factors.
Michael Michaelides
wiley +1 more source
Differential equations for families of semi-classical orthogonal polynomials within class one [PDF]
, 2017 Galina Filipuk, M.N. Rebocho
openalex +1 more source
Spline Quadrature and semi-classical orthogonal Jacobi Polynomials
, 2021 Helmut Ruhland
openalex +2 more sources
Weighted reduced rank estimators under cointegration rank uncertainty
Scandinavian Journal of Statistics, Volume 52, Issue 2, Page 595-630, June 2025.Abstract Cointegration analysis was developed for nonstationary linear processes that exhibit stationary relationships between coordinates. Estimation of the cointegration relationships in a multidimensional cointegrated process typically proceeds in two steps. First, the rank is estimated, then the auto‐regression matrix is estimated, conditionally on
Christian Holberg, Susanne Ditlevsen
wiley +1 more source
Connection coefficients for classical orthogonal polynomials of several variables [PDF]
, 2015 P. Iliev, Yuan Xu
semanticscholar +1 more source
Classical discrete orthogonal polynomials, Lah numbers, and involutory matrices
, 2003 Iván Area +3 more
openalex +1 more source