Results 151 to 160 of about 1,708,308 (346)

Graph Neural Networks at a Fraction

12 pages, 2 figures, accepted at PAKDD ...
Rucha Bhalchandra Joshi, Sagar Prakash Barad, Nidhi Tiwari, Subhankar Mishra   +3 more
openaire   +2 more sources

Graph Neural Networks on Graph Databases

CoRR
Training graph neural networks on large datasets has long been a challenge. Traditional approaches include efficiently representing the whole graph in-memory, designing parameter efficient and sampling-based models, and graph partitioning in a distributed setup. Separately, graph databases with native graph storage and query engines have been developed,
Dmytro Lopushanskyy, Borun Shi
openaire   +2 more sources

Integrated Field‐Free SOT Domain‐Wall Synapses and MTJ Stochastic Neurons for Hardware Boltzmann Machines

Advanced Functional Materials, EarlyView.
Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone, Meng Tang, Camelia Florica, Bin He, Jingkai Xu, Selma Amara, Georgian Melinte, Xixiang Zhang, Gianluca Setti   +8 more
wiley   +1 more source

Solution‐Processed Thin‐Film Transistors With Tunable Temporal Dynamics for Neuromorphic Computing

Advanced Functional Materials, EarlyView.
Solution‐processed CNT and CNT/P3HT ion‐gated transistors exhibit materials‐defined synaptic timescales: fast CNT devices for high‐frequency spiking and slow hybrid devices for temporal integration. Embedding these dynamics into coupled reservoir‐computing and spiking neural network simulations reveals that a Hybrid‐Reservoir / CNT‐SNN architecture ...
Kevin Schnittker, Haoyi Lin, Zahra Bahrami, Strahinja Marinkovic, Sung Hyun Lee, Joseph Andrews   +5 more
wiley   +1 more source

Combining Syntactic Enhancement with Graph Attention Networks for Aspect-based Sentiment Classification [PDF]

Jisuanji kexue
Aspect-level sentiment classification aims to identify the emotional polarity of a given aspect text.In this field,the combination of graph neural network and syntactic dependency parsing is one of the current hot research directions.Based on the ...
ZHANG Zebao, YU Hannan, WANG Yong, PAN Haiwei
doaj   +1 more source

Robust cross-network node classification via constrained graph mutual information

, 2022
The recent methods for cross-network node classification mainly exploit graph neural networks (GNNs) as feature extractor to learn expressive graph representations across the source and target graphs.
Yang, Shuiqiao, Jiang, Jiaojiao, Li, Jianxin, Cai, Taotao, Song, Xiangyu, Li, Bing, Cai, Borui   +6 more
core   +1 more source

Oxidized MoS2‐Based Multifunctional Memristive Hardware for Energy‐Efficient mmWave Signal Processing and In‐Memory Matrix Multiplication

Advanced Functional Materials, EarlyView.
Thermally oxidized MoS2‐based radio‐frequency switches enable a multifunctional platform that unifies broadband RF switching and in‐memory computation. The device achieves a cutoff frequency of 33.2 THz with high energy efficiency and supports hardware‐aware signal processing.
Juho Son, Changwoo Pyo, Sungmoon Park, Yoongi Cho, Seungchan Lee, Myungsoo Kim   +5 more
wiley   +1 more source

FN-GNN: A Novel Graph Embedding Approach for Enhancing Graph Neural Networks in Network Intrusion Detection Systems

Applied Sciences
With the proliferation of the Internet, network complexities for both commercial and state organizations have significantly increased, leading to more sophisticated and harder-to-detect network attacks.
Dinh-Hau Tran, Minho Park
doaj   +1 more source

Bounded graph clustering with graph neural networks

Journal of Physics: Complexity
Abstract In community detection, many methods require the user to specify the number of clusters in advance since an exhaustive search over all possible values is computationally infeasible. While some classical algorithms can infer this number directly from the data, this is typically not the case for graph neural networks (GNNs ...
Kibidi Neocosmos, Diego Baptista, Nicole Ludwig   +2 more
openaire   +2 more sources

Packed for Ossification: High‐Density Bioprinting of hPDC Spheroids in HAMA Toward Endochondral Ossification

Advanced Healthcare Materials, EarlyView.
Human periosteum‐derived cell spheroids bioprinted at high density within a hyaluronic acid matrix promote fusion and hypertrophic cartilage formation in vitro. Early encapsulation enhances spheroid interaction and matrix maturation, generating scalable cartilage templates intended for endochondral bone regeneration.
Ane Albillos Sanchez, Maria Paula Marks, Paula Casademunt, Adrián Seijas‐Gamardo, Ioannis Papantoniou, Lorenzo Moroni, Carlos Mota   +6 more
wiley   +1 more source