Our digital world is full of time series and graphs which capture the various aspects of many
complex systems. Traditionally, there are respective methods in processing these two
different types of data, eg, Recurrent Neural Network (RNN) and Graph Neural Network
(GNN), while in recent years, time series could be mapped to graphs by using the
techniques such as Visibility Graph (VG), which simultaneously captures relevant aspects of
both local and global dynamics in an easy way, so that researchers can use graph …

Our digital world is full of time series and graphs which capture the various aspects of many
complex systems. Traditionally, there are respective methods in processing these two
different types of data, eg, Recurrent Neural Network (RNN) and Graph Neural Network
(GNN), while in recent years, time series could be mapped to graphs by using the
techniques such as Visibility Graph (VG), so that researchers can use graph algorithms to
mine the knowledge in time series. Such mapping methods establish a bridge between time …