NeuralProphet is a hybrid forecasting framework based on PyTorch and trained with standard deep learning methods, making it easy for developers to extend the framework.
In this paper we present a new framework for time-series modeling that combines the best of traditional statistical models and neural networks.
Reliable uncertainty estimation for time series prediction is critical in many fields, including physics, biology, and manufacturing.
The content ranking problem in a social news website, is typically a function that maximizes a scalar metric of interest like dwell-time.
For many internet businesses, presenting a given list of items in an order that maximizes a certain metric of interest (e. g., click-through-rate, average engagement time etc.)