Results 91 to 100 of about 84,208 (297)

Dynamic Graph Attention-Aware Networks for Session-Based Recommendation

, 2020
Graph convolutional neural networks have attracted increasing attention in recommendation system fields because of their ability to represent the interactive relations between users and items.
Abugabah, Ahed, Cheng, Xiaochun, Wang, Jianfeng   +2 more
core   +1 more source

From energy provision to protein synthesis: Tunnelling nanotubes as mediators of intercellular metabolic cooperation in cancer

FEBS Open Bio, EarlyView.
The cytoskeleton‐mediated transport of mitochondria via tunnelling nanotubes restores respiration, increases ATP production, rescues cells from apoptosis, activates the AKT/mTOR signalling pathway, promotes cell migration and invasiveness, contributes to cancer progression and treatment resistance.
Stanislava Martínková, Jan Trnka
wiley   +1 more source

GAT-LI: a graph attention network based learning and interpreting method for functional brain network classification

BMC Bioinformatics, 2021
Background Autism spectrum disorders (ASD) imply a spectrum of symptoms rather than a single phenotype. ASD could affect brain connectivity at different degree based on the severity of the symptom.
Jinlong Hu, Lijie Cao, Tenghui Li, Shoubin Dong, Ping Li   +4 more
doaj   +1 more source

Structure–Function Decoupling of the Sensorimotor and Default Mode Networks in Black Americans With MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Multiple sclerosis (MS) exhibits racially disparate rates of disease progression. Black people with MS (B‐PwMS) experience a more severe disease course than non‐Hispanic White people with MS (NHW‐PwMS). Here we investigated structural and functional connectivity as well as structure–function decoupling in the ...
Emilio Cipriano, Giacomo Boffa, Maria Petracca, Marta Ponzano, Nicole Graziano, Claire Wigley, Claire Riley, Jonathan Howard, Pietro Bontempi, Sylvia Klineova, Fred Lublin, Matilde Inglese   +11 more
wiley   +1 more source

Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification

Significant challenges arise when Graph Neural Networks (GNNs) try to deal with uneven data. Specifically in signed and weighted graph structures. This makes classification tasks less effective.
Fofanah, Abdul Joseph, Chen, David, Zhang, Shaoyang, Wen, Lian   +3 more
core   +1 more source

Unsupervised Domain Adaptive Graph Convolutional Networks [PDF]

, 2020
Graph convolutional networks (GCNs) have achieved impressive success in many graph related analytics tasks. However, most GCNs only work in a single domain (graph) incapable of transferring knowledge from/to other domains (graphs), due to the challenges ...
Zhou, C, Wu, M, Wu, Man, Man Wu, Pan, S, Zhu, Xingquan, Shirui Pan, Xingquan Zhu, Chang, X, Zhou, Chuan, Xiaojun Chang, Chang, Xiaojun, Pan, Shirui, Chuan Zhou, Zhu, X   +14 more
core   +1 more source

Baseline Regional Cholinergic Denervation Predicts Cognitive Trajectories in Moderate Parkinson Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Cognitive decline is a disabling and variable feature of Parkinson disease (PD). While cholinergic system degeneration is linked to cognitive impairments in PD, most prior research reported cross‐sectional associations. We aimed to fill this gap by investigating whether baseline regional cerebral vesicular acetylcholine transporter ...
Taylor Brown, Giulia Carli, Prabesh Kanel, Stiven Roytman, Jaimie Barr, Nicolaas I. Bohnen, Roger L. Albin   +6 more
wiley   +1 more source

2021 IEEE 23rd International Conference on High Performance Computing and Communications (HPCC)

, 2022
Cross-lingual entity alignment aims at integrating complementary knowledge graphs (KGs) presented in different languages. It bridges cross-lingual knowledge for knowledge discovery.
Xiao, Jie, Wang, Biao, Zhang, Ji, Li, Zhao, Xiong, Fan, Gao, Jianliang, Liu, Xiangyue   +6 more
core   +1 more source

Posterior Cortical Atrophy in the Asia‐Pacific: A Report From the PCA Asian Workgroup

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Posterior Cortical Atrophy (PCA) is a distinct dementia syndrome primarily affecting spatial abilities and visual processing. It is associated with degeneration in the posterior part of the brain. PCA is subclassified into PCA‐pure and PCA‐plus syndromes based on consensus criteria.
Yuttachai Likitjaroen, Ya‐Ting Chang, Levinia Lim, Pai‐Yi Chiu, Jung‐Lung Hsu, SangYun Kim, Wataru Narita, Na Young Ryoo, Kyoko Suzuki, Nagaendran Kandiah, Sebastian Crutch, Ming‐Chyi Pai   +11 more
wiley   +1 more source

Context-Aware Graph Attention Networks

CoRR, 2019
Graph Neural Networks (GNNs) have been widely studied for graph data representation and learning. However, existing GNNs generally conduct context-aware learning on node feature representation only which usually ignores the learning of edge (weight) representation.
Bo Jiang 0002, Leiling Wang, Jin Tang 0001, Bin Luo 0001   +3 more
openaire   +2 more sources