Results 71 to 80 of about 302 (183)
New estimation methods for diagnostic classification models
Abstract This paper introduces a new class of estimators for cognitive diagnosis models (CDMs) based on the Cressie–Read family of ϕ$$ \phi $$‐divergences. Focusing on the loglinear CDM (LCDM), for which joint maximum likelihood estimation (JMLE) has been shown to be consistent, we propose a joint minimum divergence estimation (JMDE) framework.
Elena Castilla
wiley +1 more source
Abstract Cognitive diagnostic models (CDMs) have become essential tools for providing fine‐grained information about individuals' mastery of cognitive skills. While prior reviews have emphasized statistical foundations and deep learning‐based developments, this article focuses on recent methodological innovations designed to address persistent ...
Chun Wang, Yale Quan, David Arthur
wiley +1 more source
Computing Skinning Weights via Convex Duality
We present an alternate optimization method to compute bounded biharmonic skinning weights. Our method relies on a dual formulation, which can be optimized with a nonnegative linear least squares setup. Abstract We study the problem of optimising for skinning weights through the lens of convex duality.
J. Solomon, O. Stein
wiley +1 more source
FluidMap: Proportional and Spatially Consistent Layout Enrichments in Multidimensional Projections
FluidMap faithfully represents the frequency of an attribute and preserves spatial consistency. Current space‐filling methods over‐ or under‐represent attribute categories (i.e., all Voronoi‐based methods), sacrifice spatial consistency (i.e., Nmap) or both (i.e., Voronoi‐MWα).
Daniela Blumberg +5 more
wiley +1 more source
Building transformers from neurons and astrocytes. [PDF]
Kozachkov L, Kastanenka KV, Krotov D.
europepmc +1 more source
Control problems driven by approximately pseudo-convex multiple integral functionals
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Marghescu, Cristina-Florentina +1 more
openaire +2 more sources
Basis Networks: Learning basis functions for free‐form triangulations
Abstract We present a framework for learning compactly supported basis functions that define tangent continuous surfaces based on coarse irregular triangle meshes. The basis functions are represented as MLPs. Smoothness of the basis functions is achieved by using the values of Loop basis functions as the parameterization of the surface.
T. Djuren, M. Alexa
wiley +1 more source
<p>In this paper, we take into account the notion of strongly multiplicative convex function and derive integral inequalities of Hermite-Hadamard ($ H.H $) type for such a function in the frame of multiplicative calculus. We also develop integral inequalities of $ H.H $ type for product and quotient of strongly multiplicative convex and strongly ...
Muhammad Umar +2 more
openaire +2 more sources
Abstract While semi‐analytical boundary handling techniques have proven effective for modeling particle‐based fluid‐solid interactions, they can become unstable when applied to mesh boundaries undergoing dynamic motion or featuring complex, sharp geometries.
Junyuan Liu +5 more
wiley +1 more source
Rapid discovery of stable materials by coordinate-free coarse graining. [PDF]
Goodall REA +4 more
europepmc +1 more source

