Results 131 to 140 of about 229,000 (311)

On statistical learning of graphs

CoRR
We study PAC and online learnability of hypothesis classes formed by copies of a countably infinite graph G, where each copy is induced by permuting G's vertices. This corresponds to learning a graph's labeling, knowing its structure and label set. We consider classes where permutations move only finitely many vertices.
Vittorio Cipriani, Valentino Delle Rose, Luca San Mauro, Giovanni Soldà   +3 more
openaire   +2 more sources

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

GL-WF: A lightweight graph learning model for website fingerprinting attacks

ETRI Journal
Website fingerprinting attacks that analyze clients’ browsing preferences arean important information source for maintaining cybersecurity and improvingbig data utilization in terms of service quality.
Bo Gao, Weiwei Liu, Guangjie Liu, Fengyuan Nie, Jianan Huang, Junzhe Zhang   +5 more
doaj   +1 more source

Tester-Guided Graph Learning with End-to-End Detection Certificates for Triangle-Based Anomalies

Big Data and Cognitive Computing
We investigate anomaly detection in complex networks through a property-testing-guided graph neural model (PT-GNN) that provides an end-to-end miss-probability certificate (δ+α).
Manuel J. C. S. Reis
doaj   +1 more source

Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure

Advanced Engineering Materials, EarlyView.
Strategic geometric reinforcement transforms auxetic performance. This study evaluates 3D‐printed arrowhead metastructures, revealing that a modified design with local ring reinforcement suppresses premature failure to achieve superior energy absorption and structural efficiency.
Muhammad Gulzari, Supharoek Sornsomrit, Muhammad Ayaz Akbar, Stephan Rudykh   +3 more
wiley   +1 more source

Resilience optimization and dynamic stability defense in active distribution networks under extreme disasters: a graph learning and cooperative control approach

Frontiers in Energy Research
IntroductionThe escalating integration of high-penetration renewable energy sources introduces severe dynamic stability challenges-such as low inertia and fast transients-to modern power systems, particularly in the context of Active Distribution ...
Chutao Zheng, Wei Li, Xinsen Yang, Diwei Lin, Hao Bai, Guowei Guo   +5 more
doaj   +1 more source

Learning to Propagate for Graph Meta-Learning

CoRR, 2019
Accepted to NeurIPS 2019, code at https://github.com/liulu112601/Gated-Propagation-Net, slides at https://liulu112601.github.io/resources/GPN-NeurIPS-Slides-revised.pdf, Poster at https://liulu112601.github.io/resources/Graph-Meta-Learning-Poster-revised ...
Lu Liu 0019, Tianyi Zhou 0001, Guodong Long, Jing Jiang 0002, Chengqi Zhang   +4 more
openaire   +3 more sources

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Tensorized Consensus Graph Learning for Incomplete Multi-View Clustering with Confidence Integration

Applied Sciences
Graph-based multi-view clustering has gained significant attention in recent years due to its superior ability to reveal clustering structures. However, existing methods often incur high computational costs when capturing local information and overlook ...
Guangqi Jiang, Huijie Jiang, Wangjie Chen, Zijie Chen   +3 more
doaj   +1 more source

Texoskeletons: Developing the Fundamental Technologies for Creating Intelligent Soft Robotic Clothing With Integrated 1D Sensors and Actuators

Advanced Functional Materials, EarlyView.
ABSTRACT Traditional wearable exoskeletons rely on rigid structures, which limit comfort, flexibility, and everyday usability. This work introduces the fundamental technologies to create the first soft, lightweight, intelligent textile‐based exoskeletons (Texoskeletons) built using 1D sensors and actuators.
Amy Lukomiak, Rameesh Bulathsinghala, Jack Varga, Shuxin Meng, Kalana Marasinghe, Imaad Refai, Biyon Fernando, Amitkumar Patel, Chamika M. Halloluwa‐Arachchige, Carlos Oliveira, Arash M. Shahidi, Zahra Rahemtulla, Alexander Turner, Ziyun Ding, Bernard X. W. Liew, Andy Kerr, Ezio Preatoni, Theo Hughes‐Riley, Ishara Dharmasena, Pasindu Lugoda   +19 more
wiley   +1 more source