EUN-HU KIM

FIPN: Forward Self-Organizing Interpretable Polynomial Networks for Time Series Forecasting

Most existing time series forecasting models are trained with backpropagation, which often brings high computational cost and limited transparency, so it can be hard to understand why a model makes a given prediction. This paper presents FIPN, a forward self-organizing interpretable polynomial netwo…