Results 111 to 120 of about 601,015 (329)
On binary decision hypertree (hyperdiagram) [PDF]
In computer science, a binary decision diagram is a data structure that is used to represent a Boolean function and to consider a compressed representation of relations.
Mohammad Hamidi, Marzieh Rahmati
doaj +1 more source
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Political Influence in Multi-Choice Institutions: Cyclicity, Anonymity and Transitivity [PDF]
We study political influence in institutions where members choose from among several options their levels of support to a collective goal, these individual choices determining the degree to which the goal is reached.
Diffo Lambo, Lawrence +2 more
core +1 more source
The Relations between Superheroes and Their Enemies as an Analogy of Binary Opposition Relationship [PDF]
Sayid Mataram, Deny Tri Ardianto
openalex +1 more source
Intelligent Supportive System for People with Profound Intellectual and Multiple Disabilities
A holistic INSENSION system is developed—a novel intelligent decision support system leveraging state‐of‐the‐art noninvasive audio‐visual sensor technologies together with machine learning algorithms and expert knowledge, to detect and interpret behaviors and communications (nonverbal signals—NVSs) of people with PIMD in challenging real‐world ...
Gašper Slapničar +10 more
wiley +1 more source
This work harnesses nonidealities in analog in‐memory computing (IMC) by training physical neural networks modeled with ordinary differential equations. A differentiable spike‐time discretization accelerates training by 20× and reduces memory usage by 100×, enabling large IMC‐equivalent models to learn the CIFAR‐10 dataset.
Yusuke Sakemi +5 more
wiley +1 more source
This study introduces a framework that combines graph neural networks with causal inference to forecast recurrence and uncover the clinical and pathological factors driving it. It further provides interpretability, validates risk factors via counterfactual and interventional analyses, and offers evidence‐based insights for treatment planning ...
Jubair Ahmed +3 more
wiley +1 more source
Elastic Fast Marching Learning from Demonstration
This article presents Elastic Fast Marching Learning (EFML), a novel approach for learning from demonstration that combines velocity‐based planning with elastic optimization. EFML enables smooth, precise, and adaptable robot trajectories in both position and orientation spaces.
Adrian Prados +3 more
wiley +1 more source

