Joint Modeling of Event Sequence and Time Series with Attentional Twin Recurrent Neural Networks

A variety of real-world processes (over networks) produce sequences of data whose complex temporal dynamics need to be studied. More especially, the event timestamps can carry important information about the underlying network dynamics, which otherwise are not available from the time-series evenly sampled from continuous signals... (read more)

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