Graph neural networks (GNNs) have emerged as a state-of-the-art data-driven tool for modeling connectivity data of graph-structured complex networks and integrating information of their nodes and edges in space and time. However, as of yet, the analy...
The CutMix technique is a sophisticated approach for augmenting data in order to train neural network-based image classifiers. Essentially, it involves cutting out a portion of a random image and pasting it into the same location as another image. Ho...
In recent years, research on community structure for complex networks has received increasing greater attention, and the overlapping community structure is more closely related to the actual social structure than the non-overlapping community structu...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Aug 6, 2025
The endogenous aspect of social influence, reflected in the spontaneous alignment of behaviors within close social relationships, plays a crucial role in understanding human social behavior. In two studies involving 222 human subjects (Study 1: = 17...
Neural networks : the official journal of the International Neural Network Society
Apr 27, 2025
Weak ties that bridge different communities are crucial for preserving global connectivity, enhancing resilience, and maintaining functionality and dynamics of complex networks, However, making accurate link predictions for weak ties remain challengi...
Recommender Systems (RS) aim to predict users' latent interests in items by learning embeddings from user-item graphs. Graph Neural Networks (GNNs) have significantly advanced RS by enabling the embedding of graph-structured data. However, relying so...
The evolution experienced by global society, in the post-COVID 19 era, is marked by the quite obligatory use of digital media in many sectors, as is the case for the health sector. Quite frequently, both patients and health professionals use social m...
Psychiatry and clinical neurosciences
Feb 25, 2025
AIM: Social anxiety disorder (SAD) is a mental disorder that requires early detection and treatment. However, some individuals with SAD avoid face-to-face evaluations, which leads to delayed detection. We aim to predict individuals with SAD based on ...
Neural networks : the official journal of the International Neural Network Society
Feb 5, 2025
Aiming to identify corresponding users in different networks, social network alignment is significant for numerous subsequent applications. Most existing models apply consistency assumptions on undirected networks, ignoring platform disparity caused ...
BACKGROUND: Social networking services (SNS) closely reflect the lives of individuals in modern society and generate large amounts of data. Previous studies have extracted drug information using relevant SNS data. In particular, it is important to de...
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