41 citations · 52 across the 13 of their papers we have counts for
6 papers · 1 filter
Variational Bayesian Inference for Mixed Logit Models with Unobserved Inter- and Intra-Individual Heterogeneity
Rico Krueger, Prateek Bansal, Michel Bierlaire +2
Variational Bayes (VB), a method originating from machine learning, enables fast and scalable estimation of complex probabilistic models. Thus far, applications of VB in discrete c…
Can Mobility-on-Demand services do better after discerning reliability preferences of riders?
Prateek Bansal, Yang Liu, Ricardo Daziano +1
We formalize one aspect of reliability in the context of Mobility-on-Demand (MoD) systems by acknowledging the uncertainty in the pick-up time of these services. This study answers…
Eliciting Preferences of Ridehailing Users and Drivers: Evidence from the United States
Prateek Bansal, Akanksha Sinha, Rubal Dua +1
Transportation Network Companies (TNCs) are changing the transportation ecosystem, but micro-decisions of drivers and users need to be better understood to assess the system-level…
Pólygamma Data Augmentation to address Non-conjugacy in the Bayesian Estimation of Mixed Multinomial Logit Models
Prateek Bansal, Rico Krueger, Michel Bierlaire +2
The standard Gibbs sampler of Mixed Multinomial Logit (MMNL) models involves sampling from conditional densities of utility parameters using Metropolis-Hastings (MH) algorithm due…
A Generalized Continuous-Multinomial Response Model with a t-distributed Error Kernel
Subodh Dubey, Prateek Bansal, Ricardo A. Daziano +1
In multinomial response models, idiosyncratic variations in the indirect utility are generally modeled using Gumbel or normal distributions. This study makes a strong case to subst…
Bayesian Estimation of Mixed Multinomial Logit Models: Advances and Simulation-Based Evaluations
Prateek Bansal, Rico Krueger, Michel Bierlaire +2
Variational Bayes (VB) methods have emerged as a fast and computationally-efficient alternative to Markov chain Monte Carlo (MCMC) methods for scalable Bayesian estimation of mixed…