Adapting to the stream: An instance-attention GNN method for irregular multivariate time series data
Framework of DynIMTS. The model is a recurrent structure based on a spatial-temporal encoder and consists of three main components: embedding learning, spatial-temporal learning, and graph learning.
A review by researchers at Tongji University and the University of Technology Sydney highlights the powerful role of Graph Neural Networks (GNNs) in exposing financial fraud. By revealing intricate ...
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