Integrable Elasticity via Neural Demand Potentials

Abstract:We propose the Integrable Context-Dependent Demand Network (ICDN), a demand-first neural model for multiproduct retail demand. ICDN learns log-demand as a smooth, context-conditioned function of log-prices, allowing elasticities to be derived exactly from the learned demand surface. Across three retail datasets, the model achieves competitive out-of-sample prediction while producing analytically tractable, and economically regularized own- and cross-price responses.

Machine Learning (cs.LG)

arXiv:2605.22820 [cs.LG]

(or arXiv:2605.22820v2 [cs.LG] for this version)

https://doi.org/10.48550/arXiv.2605.22820 Focus to learn more arXiv-issued DOI via DataCite

https://doi.org/10.1016/j.eswa.2026.134600 Focus to learn more DOI(s) linking to related resources

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