In the world around us, many things exist in the context of time: a bird's path through the sky is understood as different positions over a period of time, and conversations as a series of words ...

This study bridges classical time-series econometrics with modern machine learning by establishing theoretical performance guarantees for recurrent neural networks (RNNs) applied to complex ...