The rapid identification of respiratory virus outbreaks is needed to enable rational and effective public health interventions. We developed new quantitative approaches for simultaneous ...

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Classic Protocol Published: November 2005 Long and accurate polymerase chain reaction Nature Methods 2, 885–886 (2005) Cite this article ...

Graph convolutional network (GCN) outputs powerful representation by considering the structure information of the data to conduct representation learning, but its robustness is sensitive to the ...

Graph embedding, aiming to learn low-dimensional representations (aka. embeddings) of nodes in graphs, has received significant attention. In recent years, there has been a surge of efforts, among ...

Network Service Providers (NSPs) envisage to support the divergent and stringent requirements of future services by instantiating these services as service chains, commonly referred to as Service ...

Multimodal recommendation systems have made significant progress by leveraging graph convolutional networks to integrate user behavior with item content, including images and text. However, these ...

Graph Neural Networks (GNNs) have gained attention for their ability in capturing node interactions to generate node representations. However, their performances are frequently restricted in ...

Human emotion is expressed, perceived and captured using a variety of dynamic data modalities, such as speech (verbal), videos (facial expressions) and motion sensors (body gestures). We propose a ...