Amortized-MXL: Scaling Bayesian Inference of Mixed Multinomial Logit Models to Very Large Datasets

An Amortized Variational Inference approach for scaling Bayesian inference in Mixed Multinomial Logit models to very large datasets and to increase the flexibility of the posterior approximations as proposed in the paper:

Check out the GitHub project for further details.

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CONTACT:

Please send questions and comments to rodr [at] dtu.dk