Results 31 to 40 of about 4,757 (89)
The joint survival super learner: A super learner for right‐censored data
ABSTRACT Risk prediction models are widely used to guide real‐world decision‐making in areas such as healthcare and economics, and they also play a key role in estimating nuisance parameters in semiparametric inference. The super learner is a machine learning framework that combines a library of prediction algorithms into a meta‐learner using cross ...
Anders Munch, Thomas A. Gerds
wiley +1 more source
Monodromy zeta functions at infinity, Newton polyhedra and constructible sheaves [PDF]
By using sheaf-theoretical methods such as constructible sheaves, we generalize the formula of Libgober-Sperber concerning the zeta functions of monodromy at infinity of polynomial maps into various directions.
Matsui, Yutaka, Takeuchi, Kiyoshi
core +1 more source
ABSTRACT Introduction School refusal affects many children and adolescents receiving psychiatric care; however, predictors of new‐onset refusal and successful return during treatment remain unclear. This retrospective cohort study identified factors associated with (1) developing school refusal among initially attending patients and (2) returning to ...
Yoshinori Sasaki +10 more
wiley +1 more source
The Kazhdan-Lusztig conjecture for finite W-algebras
We study the representation theory of finite W-algebras. After introducing parabolic subalgebras to describe the structure of W-algebras, we define the Verma modules and give a conjecture for the Kac determinant.
B. L. Feigin +16 more
core +2 more sources
Efficient Dynamics: Reduced‐Order Modeling of the Time‐Dependent Schrödinger Equation
Reduced‐order modeling (ROM) approaches for the time‐dependent Schrödinger equation are investigated, highlighting their ability to simulate quantum dynamics efficiently. Proper Orthogonal Decomposition, Dynamic Mode Decomposition, and Reduced Basis Methods are compared across canonical systems and extended to higher dimensions.
Kolade M. Owolabi
wiley +1 more source
Convergence properties of dynamic mode decomposition for analytic interval maps
Abstract Extended dynamic mode decomposition (EDMD) is a data‐driven algorithm for approximating spectral data of the Koopman operator associated to a dynamical system, combining a Galerkin method with N$N$ functions and a quadrature method with M$M$ quadrature nodes.
Elliz Akindji +3 more
wiley +1 more source
This paper introduces the Fractional Novel Analytical Method (FNAM), a Taylor‐series‐based technique for approximating nonlinear fractional differential‐difference equations. Built on the Caputo derivative, FNAM achieves rapid convergence without relying on Adomian polynomials, perturbation schemes, or transform methods.
Uroosa Arshad +3 more
wiley +1 more source
Poles of Archimedean zeta functions for analytic mappings
In this paper, we give a description of the possible poles of the local zeta function attached to a complex or real analytic mapping in terms of a log-principalization of an ideal associated to the mapping.
Leon-Cardenal, E. +2 more
core +1 more source
Robust estimation of a Markov chain transition matrix from multiple sample paths
Markov chains are fundamental models for stochastic dynamics, with applications in a wide range of areas such as population dynamics, queueing systems, reinforcement learning, and Monte Carlo methods. Estimating the transition matrix and stationary distribution from observed sample paths is a core statistical challenge, particularly when multiple ...
Lasse Leskelä, Maximilien Dreveton
wiley +1 more source
Abstract We address the problem of regularity of solutions ui(t,x1,…,xN)$u^i(t, x^1, \ldots, x^N)$ to a family of semilinear parabolic systems of N$N$ equations, which describe closed‐loop equilibria of some N$N$‐player differential games with Lagrangian having quadratic behaviour in the velocity variable, running costs fi(x)$f^i(x)$ and final costs gi(
Marco Cirant, Davide Francesco Redaelli
wiley +1 more source

