GNN-DCMs apply graph neural networks to discrete choice modeling, recovering nested logit and spatially correlated logit via message passing on utilities and demonstrating better predictive performance for residential location choices in Chicago.
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Graph neural networks for residential location choice: connection to classical logit models
GNN-DCMs apply graph neural networks to discrete choice modeling, recovering nested logit and spatially correlated logit via message passing on utilities and demonstrating better predictive performance for residential location choices in Chicago.