Integrable Elasticity via Neural Demand Potentials

The paper introduces the Integrable Context-Dependent Demand Network (ICDN), a neural model that predicts multiproduct retail demand by learning log‑demand as a smooth, context‑conditioned function of log‑prices. This approach allows elasticities to be derived exactly from the learned demand surface, yielding analytically tractable and economically regularized own‑ and cross‑price responses. Across three retail datasets, ICDN achieves competitive out‑of‑sample prediction performance.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.