Results 41 to 50 of about 29,440 (144)
Enhancing generalized spectral clustering with embedding Laplacian graph regularization
CAAI Transactions on Intelligence Technology, EarlyView.Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang +5 more
wiley +1 more source
A Universal Meta‐Heuristic Framework for Influence Maximisation in Hypergraphs
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Influence maximisation (IM) aims to select a small number of nodes that are able to maximise their influence in a network and covers a wide range of applications. Despite numerous attempts to provide effective solutions in simple networks, higher‐order interactions between entities in various real‐world systems are usually not taken into ...
Ming Xie +5 more
wiley +1 more source
On the present state of the Andersen-Lempert theory
, 2010 In this survey of the Andersen-Lempert theory we present the state of the art in the study of the density property (which means that the Lie algebra generated by completely integrable holomorphic vector fields on a given Stein manifold is dense in the ...
Kaliman, Shulim, Kutzschebauch, Frank
core
Real Estate Economics, EarlyView.Abstract We estimate the price impact of very nearby concurrently listed properties in the Sydney housing market and assess their competition effects. We apply a hedonic model with spatiotemporal effects regularized via a graph Laplacian prior at the month‐by‐SA2 regional level to seven SA4 subregions of metropolitan Sydney. The model structure enables
Willem P. Sijp, Mengheng Li
wiley +1 more source
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
International Statistical Review, EarlyView.Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source
Image of mathematics: A case study of two women's early mathematics experiences
School Science and Mathematics, EarlyView.Abstract People often view mathematics as abstract, cold, and irrelevant to real life, and their school experiences likely influence such views. In this case study, we investigated the mathematics experiences of two women who participated in an afterschool girls‐only STEM club 30 years ago when they were in fifth and sixth grades.
Lili Zhou +4 more
wiley +1 more source
Secondary School Mathematics Teachers' Accuracy at Predicting Student Errors
School Science and Mathematics, EarlyView.ABSTRACT We studied changes over time in secondary school mathematics teachers' accuracy in predicting students' errors. In a total of 37 sessions, seven teachers were asked to predict the percentage of students choosing each option in five multiple‐choice diagnostic questions taken from the free website https://diagnosticquestions.com/.
Aidan Stannard, Colin Foster
wiley +1 more source
The Journal of Physiology, EarlyView.Abstract figure legend Schematic overview of the experimental and computational framework for investigating hiPSC‐CM electrophysiology with MEA systems. The MEA‐based model integrates experimental data with phenotype‐specific ionic models and tissue‐level heterogeneity.
Sofia Botti +2 more
wiley +1 more source
Rational points on even‐dimensional Fermat cubics
Transactions of the London Mathematical Society, Volume 13, Issue 1, December 2026.Abstract We show that even‐dimensional Fermat cubic hypersurfaces are rational over any field of characteristic not equal to three, by constructing explicit rational parameterizations with polynomials of low degree. As a byproduct of our rationality constructions, we obtain estimates for the number of their rational points over a number field and ...
Alex Massarenti
wiley +1 more source
Topological Graph Neural Networks: A Novel Approach for Geometric Deep Learning
Applied AI Letters, Volume 7, Issue 2, June 2026.This graphical abstract illustrates the Topological Graph Neural Network (TopGNN) architecture. It demonstrates a parallel processing approach where an input graph is simultaneously analyzed by a standard GNN Encoder to capture local node features and by Persistent Homology to extract global topological features (like cycles and voids), visualized as a
Amarjeet +7 more
wiley +1 more source