Leveraging variational autoencoders and recurrent neural networks for demand forecasting in supply chain management: A case study

Accurate demand forecasting is key for companies to optimize inventory management and satisfy customer demand efficiently. This paper aims to Investigate on the application of generative AI models in demand forecasting. Two models were used: Long Short-Term Memory (LSTM) networks and Variational Aut