Results 181 to 190 of about 18,832 (283)

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, Anurag Sinha, Khalid Hussain, Wasim Ahmad Bhat, Sudhanshu Maurya, Mohammad Nadeem Ahmed, Mohammad Rashid Hussain, S. Khalid   +7 more
wiley   +1 more source

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

Applied AI Letters, Volume 7, Issue 2, June 2026.
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

Photocatalytic and Photo-Fenton Degradation Activity of Hierarchically Structured α-Fe₂O₃@Fe-CeO₂ and g-C₃N₄ Composite. [PDF]

Int J Mol Sci
Bužková A, Pocklanová R, Novák V, Petr M, Štefková B, Rancová A, Kašlík J, Prucek R, Panáček A, Kvítek L.   +9 more
europepmc   +1 more source

Atomic‐Level Insight of Carbon‐Based Anodes for Advanced Sodium Storage: Electrochemical Mechanisms and Molecular Simulation‐Assisted Modification

cMat, Volume 3, Issue 2, June 2026.
Hard carbon is a promising anode for sodium‐ion batteries, yet its Na+ storage mechanism remains elusive. This review summarizes Na+ storage behavior in hard carbon from first‐principles (DFT) calculations, establishes structure–function relationships, summarizes DFT‐based evaluation methods, and provides perspectives for the rational theoretical ...
Yuefang Chen, Guoping Liu, Yuwen Zhao, Mengmeng Zhang, Yifang Zhang, Zhenyang Yu, Zhijia Zhang, Huijun Li, Yong Jiang   +8 more
wiley   +1 more source

Autonomic Signature-Driven Anesthesia Depth Monitoring with Biomimetic Wearable ECG and Knowledge Graph-Augmented Deep Networks. [PDF]

Sensors (Basel)
Bao A, Ding C.
europepmc   +1 more source

GCN-DevLSTM: Path Development for Skeleton-Based Action Recognition

Skeleton-based action recognition (SAR) in videos is an important but challenging task in computer vision. The recent state-of-the-art (SOTA) models for SAR are primarily based on graph convolutional neural networks (GCNs), which are powerful in ...
Zhang, Xin, Yang, Weixin, Ni, Hao, Jiang, Lei   +3 more
core  

Leveraging Hamiltonian neural flow for robust single-cell multi-omics integration: application to Alzheimer's disease. [PDF]

Front Genet
Huang Z, Kong W, Wang S.
europepmc   +1 more source

Graph Model‐Based Edge Node Pilot Attack Tracing Technology of Power Terminal Embedded Components

Engineering Reports, Volume 8, Issue 6, June 2026.
A graph model‐based pilot attack‐tracing method for power terminal embedded components is proposed, integrating dynamic trust adjustment with random‐walk graph embedding. The approach achieves high detection probability (0.999 at 400 iterations) and robust anti‐attack capability (≥ 0.97) while maintaining < 2.0% packet loss, enabling efficient edge ...
Peng Xiao, Jian Hu, Li Liu
wiley   +1 more source

A lightweight Chinese-English translation model integrating compressed BERT attention and phrase discard mechanism. [PDF]

Front Neurorobot
Qi X, Bao H.
europepmc   +1 more source

Optimizing the Collaborative Supply Scheduling of Renewable Energy in the Tourism Industry Chain Using Graph Neural Networks

Engineering Reports, Volume 8, Issue 6, June 2026.
Typical configuration of Huangshan Scenic Area. ABSTRACT To cope with the supply and demand imbalance challenge caused by the surge in energy demand in tourism‐intensive areas and the high volatility of renewable energy, this paper aims to construct a collaborative scheduling optimization model based on graph neural networks (GNNs). The model abstracts
Lixia Wang
wiley   +1 more source