Multimodal Neural Network For Demand Forecasting. (arXiv:2210.11502v1 [cs.LG])

Demand forecasting applications have immensely benefited from the
state-of-the-art Deep Learning methods used for time series forecasting.
Traditional uni-modal models are predominantly seasonality driven which attempt
to model the demand as a function of historic sales along with information on
holidays and promotional events. However, accurate and robust sales forecasting
calls for accommodating multiple other factors, such as natural calamities,
pandemics, elections, etc., impacting the demand for products and product
categories in general. We propose a multi-modal sales forecasting network …

arxiv demand forecasting forecasting multimodal network neural network