Predicting a Time-Dependent Quantity Using Recursive Generative Query Network.

We propose here a novel neural architecture dedicated to the prediction of time series. It can be considered as an adaptation of the idea of (GQN) to the data which is of a sequence nature. The new approach, dubbed here as the (RGQN), allows for efficient prediction of time series.