Time Series Forecasting using Recurrent Neural Networks modified by Bayesian Inference in the Learning Process

Typically, time series forecasting is done by using models based directly on the past observations from the same sequence. In these cases, when the model is learning from data, there is not an extra quantity of noiseless data available and computational resources are unlimited. In practice, it is ne...