  Bike sharing systems often suffer from poor capacity management as a result
of variable demand. These bike sharing systems would benefit from models to
predict demand in order to moderate the number of bikes stored at each station.
In this paper, we attempt to apply a graph neural network model to predict bike
demand in the New York City, Citi Bike dataset.
