Abstract: In recent years, Graph Neural Networks (GNNs) have achieved significant success in graph-based tasks. However, they still face challenges in complex scenarios, particularly in integrating ...
Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. Changes in gut microbiota composition have ...
In this study, a novel self-cumulative contrastive graph clustering (SC-CGC) method is devised, which is capable of dynamically adjusting the influence of neighbors with different hops. Our intuition ...
When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. It is a truth universally acknowledged, that a single TV in need of decent sound, must be ...
What do you do when your bar is a wreck? What do you do when you’re drowning in debt? What do you do when your staff is a mess? You call Jon Taffer at Bar Rescue. It’s far from closing time ...
Initially, time-frequency complexity and temporal features of the EEG signal are extracted to generate node features for a graph convolutional network. Subsequently, leveraging channel correlation, ...
and the top 100 cumulative clone frequency. An intriguing question that arises from the IGH repertoire dynamics upon vaccination is where do the population of B cells in the expanded IGH lineages come ...
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