Results 141 to 150 of about 120,918 (284)
An extension of the basic local independence model to multiple observed classifications
Abstract The basic local independence model (BLIM) is appropriate in situations where populations do not differ in the probabilities of the knowledge states and the probabilities of careless errors and lucky guesses of the items. In some situations, this is not the case. This work introduces the multiple observed classification local independence model
Pasquale Anselmi +8 more
wiley +1 more source
Existence and non-existence results for a nonlinear heat equation
In this study, we consider the nonlinear heat equation $$displaylines{ u_{t}(x,t) = Delta u(x,t) + u(x,t)^p quad hbox{in } Omega imes (0,T),cr Bu(x,t) = 0 quad hbox{on } partialOmega imes (0,T),cr u(x,0) = u_0(x) quad hbox{in } Omega,}$$ with ...
Canan Celik
doaj
From tetrachoric to kappa: How to assess reliability on binary scales
Abstract Reliability is crucial in psychometrics, reflecting the extent to which a measurement instrument can discriminate between individuals or items. While classical test theory and intraclass correlation coefficients are well‐established for quantitative scales, estimating reliability for binary outcomes presents unique challenges due to their ...
Sophie Vanbelle
wiley +1 more source
Abstract Hidden Markov diagnostic classification models capture how students' cognitive attributes evolve over time. This paper introduces a Bayesian Markov chain Monte Carlo algorithm for diagnostic classification models that jointly estimates time‐varying Q matrices, latent attributes, item parameters, attribute class proportions and transition ...
Chen‐Wei Liu
wiley +1 more source
LLM‐based prior elicitation for Bayesian graphical modeling
ABSTRACT In the Bayesian graphical modeling framework, priors on network structure encode theoretical assumptions and uncertainty about the topology of psychological constructs under study. For instance, the Bernoulli prior specifies the probability of each pairwise interaction, the Beta–Bernoulli prior governs expected network density, and the ...
Nikola Sekulovski +2 more
wiley +1 more source
Hierarchical Differentiable Fluid Simulation
We introduce a two‐step algorithm that significantly reduces memory usage for solving control problems using differentiable fluid simulation techniques: our method first optimizes for bulk forces at reduced resolution, then refines local details over sub‐domains while maintaining differentiability. In trading runtime for memory, it enables optimization
Xiangyu Kong +4 more
wiley +1 more source
Real‐Time Conformal Maps and Parameterizations
Abstract We present a simple algorithm to conformally map between two simple and bounded planar domains based on the concept of harmonic measure, which is a conformal invariant. With suitable preprocessing, the algorithm is fast enough to compute all possible conformal maps (having three real degrees of freedom) between the two domains in real time in
Q. Chang, C. Gotsman, K. Hormann
wiley +1 more source
Symmetry theorems via the continuous steiner symmetrization
Using a new approach due to F. Brock called the Steiner symmetrization, we show first that if $u$ is a solution of an overdetermined problem in the divergence form satisfying the Neumann and non-constant Dirichlet boundary conditions, then $Omega$ is an ...
L. Ragoub
doaj
Discontinuous Boundary Conditions and the Dirichlet Problem [PDF]
openaire +1 more source
Fast Injective Mesh Parameterization via Beltrami Coefficient Prolongation
Abstract We present a highly efficient and robust method for free boundary injective parameterization of disk‐like triangle meshes with low isometric distortion. Harmonic function–based approaches, grounded in a strong mathematical framework, are widely employed.
G. Fargion, O. Weber
wiley +1 more source

