Results 151 to 160 of about 24,126 (306)
Locality regularization graph embedding in face verification
Graph embedding techniques attempt to construct a high locality projection in such a way that projected same class samples should be close to each other.
Teoh, Andrew Beng Jin +4 more
core
ABSTRACT Autism spectrum disorder (ASD) is characterized by alterations in social understanding and self‐related experience that overlap with broader dimensions of psychosocial vulnerability. These domains are tightly interconnected, motivating the use of analytic approaches that can capture their organization as complex associations rather than as ...
Szilárd Holka +4 more
wiley +1 more source
Machine Learning Paradigm for Advanced Battery Electrolyte Development
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su +4 more
wiley +1 more source
Graph-Based Regularization of Binary Classifiers for Texture Segmentation
International audienceIn this paper, we propose to improve a recent texture-based graph regularization model used to perform image segmentation by including a binary classifier in the process.
Boné, Romuald +2 more
core
Machine‐learning potentials are increasingly taking on the exploratory tasks of homogeneous catalysis, enabling rapid conformer sampling and reaction‐space mapping. However, when selectivity depends on subtle electronic effects, electronic‐structure methods remain essential.
Maxime Ferrer +3 more
wiley +1 more source
AbstractH.M. Mulder introduced (0,λ)-graphs and proved that maximum (0,λ)-graphs are hypercubes. One way of generalization of this concept is to consider cycle-regular graphs. We prove that these graphs have also some regularity properties and that maximum [3, 1, 6]-cycle regular graphs are also related to hypercubes.
openaire +1 more source
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos +3 more
wiley +1 more source
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales +6 more
wiley +1 more source
A spanning subgraph F of a graph G is called a [k-1,k]-factor if \(k-1\leq d_ F(x)\leq k\) for all vertices of x of G, where \(d_ F(x)\) denotes the degree of x in F. \textit{W. T. Tutte} [The subgraph problem, Ann. Discrete Math. 3, 289-295 (1978; Zbl 0377.05034)] proved that if r is an odd integer, then every r-regular graph has a [k-1,k]-factor for ...
openaire +3 more sources

