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Amortized Inference for Correlated Discrete Choice Models via Equivariant Neural Networks
Discrete choice models are fundamental tools in management science, economics, and marketing for understanding and predicting decision-making. Logit-based models are dominant in applied work, largely due to their convenient closed-form expressions for choice probabilities. However, they impose restr
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