What has Changed from Prophet#

NeuralProphet has a number of added features with respect to original Prophet. They are as follows.

  • Gradient Descent for optimisation via using PyTorch as the backend.

  • Modelling Auto-Regression of time series using AR-Net

  • Modelling lagged regressors using a separate linear or Feed-Forward Neural Network.

  • Directly predict specific forecast horizons.

  • Train a single model on many related time-series (global modelling).

Due to the modularity of the code and the extensibility supported by PyTorch, any component trainable by gradient descent can be added as a module to NeuralProphet. Using PyTorch as the backend, makes the modelling process much faster compared to original Prophet which uses Stan as the backend.