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  1. Probabilistic machine learning combines flexible probability models with scalable machine learning methods to model consumer choices. The paper reviews applications to heterogeneity, nonlinear dynamics, unstructured data, missingness, representation learning, causal inference, and decision-making. Publisher-formatted article-in-press PDF with DOI; final issue citation: International Journal of Research in Marketing 43(2), 462–484 (2026). 
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    Free, publicly-accessible full text available June 1, 2027
  2. Free, publicly-accessible full text available December 1, 2026