Results 121 to 130 of about 1,049,471 (309)

H-GAT: A Hardware-Efficient Accelerator for Graph Attention Networks

Journal of Applied Science and Engineering
Recently, Graph Attention Networks (GATs) have shown good performance for representation learning on graphs. Furthermore, GAT leverage the masked self-attention mechanism to get a more advanced feature representation than the graph convolution networks ...
Shizhen Huang, Enhao Tang, Shun Li
doaj   +1 more source

Mechanochemical Synthesis and Characterization of Nanostructured ErB4 and NdB4 Rare‐Earth Tetraborides

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
ErB4 and NdB4 nanostructured powders are produced by mechanochemical synthesis. 5 h mechanical alloying and 4 M HCl acid leaching are used in the production. ErB4 and NdB4 powders exhibit maximum magnetization of 0.4726 emu g−1 accompanied with an antiferromagnetic‐to‐paramagnetic phase transition at about TN = 18 K and 0.132 emu g−1 with a maximum at ...
Burçak Boztemur, Faruk Kaya, Bora Derin, Mustafa Lütfi Öveçoğlu, Ju Li, Duygu Ağaoğulları   +5 more
wiley   +1 more source

Graph-aware isomorphic attention for adaptive dynamics in transformers

APL Machine Learning
We present an approach for modifying transformer architectures by integrating graph-aware relational reasoning into the attention mechanism, merging concepts from graph neural networks and language modeling ...
Markus J. Buehler
doaj   +1 more source

Harnessing Fungal Biowelding for Constructing Mycelium‐Engineered Materials

Advanced Engineering Materials, EarlyView.
Mycelium‐bound composites (MBCs) offer low‐carbon alternatives for construction, yet interfacial bonding remains a critical challenge. This review examines fungal biowelding as a biocompatible adhesive, elucidating mycelium‐mediated interfacial mechanisms and their role in material assembly. Strategies to optimize biowelding are discussed, highlighting
Xue Brenda Bai, Xinrui Sarah Niu, Zhao Qin   +2 more
wiley   +1 more source

Link Performance Prediction of Power Fiber Optic Communication System Based on Attention Mechanism and Convolutional Neural Network Fusion

Electrica
In order to enhance the multi-objective optimization capability of power communication transmission networks, the author proposes an optimization method that integrates improved graph neural networks (GNNs) and genetic algorithms (GAs).
Yong Zhang, Yan Liu, Chunying Wang, Jiaojiao Dong   +3 more
doaj   +1 more source

Jointly Multiple Events Extraction via Attention-based Graph Information Aggregation

, 2018
Event extraction is of practical utility in natural language processing. In the real world, it is a common phenomenon that multiple events existing in the same sentence, where extracting them are more difficult than extracting a single event.
Huang, Heyan, Liu, Xiao, Luo, Zhunchen
core  

Hyperbolic Heterogeneous Graph Attention Networks

Companion Proceedings of the ACM Web Conference 2024
Accepted in ACM THE WEB CONFERENCE 2024 short paper ...
Jongmin Park, Seunghoon Han, Soohwan Jeong, Sungsu Lim   +3 more
openaire   +2 more sources

Packaging of Macroscopic Material Payloads: Needs, Challenges, Concepts, and Future Directions

Advanced Engineering Materials, EarlyView.
This review introduces a unified framework that decomposes any macroscopic packaging system into the payload, packaging material, and packaging strategy and combines them into a conceptual packaging equation: packaging strategy = payload + packaging material.
Venkata S. R. Jampani, Manos Anyfantakis
wiley   +1 more source

Tribological Performance of 60NiTi Alloy Under Varying Contact Conditions and Elevated Temperatures in Linear Reciprocating Sliding

Advanced Engineering Materials, EarlyView.
This study investigates the tribological response of 60NiTi alloy under dry, water‐lubricated and high‐temperature conditions. The alloy exhibits decreasing wear volume and friction with increasing temperature due to the formation of protective oxide layers. The work clarifies dominant wear mechanisms and demonstrates the suitability of 60NiTi for high‐
Anthony Onyebuchi Okoani, Miguel Angel Selles, Maziar Ramezani   +2 more
wiley   +1 more source

GTAT: empowering graph neural networks with cross attention

Scientific Reports
Graph Neural Networks (GNNs) serve as a powerful framework for representation learning on graph-structured data, capturing the information of nodes by recursively aggregating and transforming the neighboring nodes’ representations.
Jiahao Shen, Qura Tul Ain, Yaohua Liu, Banqing Liang, Xiaoli Qiang, Zheng Kou   +5 more
doaj   +1 more source