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Tim Hillel technical reports
This page reports only the academic work registered in the databases of the Transport and Mobility Laboratory, and is not necessarily a comprehensive list of the work by Tim Hillel.
More information may be available here
\item[Rezvany et al., 2023]
Rezvany, N., Bierlaire, M., and Hillel, T. (2023). Simulating intra-household interactions for in- and out-of-home
activity scheduling. Technical report . )
\item[Pougala et al., 2022]
Pougala, J., Hillel, T., and Bierlaire, M. (2022). OASIS: Optimisation-based Activity Scheduling
with Integrated Simultaneous choice dimensions. Technical report TRANSP-OR 221124. )
\item[Manser et al., 2021]
Manser, P., Haering, T., Hillel, T., Pougala, J., Krueger, R., and Bierlaire, M. (2021). Resolving temporal scheduling conflicts in activity-based modelling. Technical report TRANSP-OR 211209. )
\item[Bierlaire et al., 2021]
Bierlaire, M., Frejinger, E., and Hillel, T. (2021). Dynamic choice models. Technical report TRANSP-OR 210305. )
\item[Pougala et al., 2021]
Pougala, J., Hillel, T., and Bierlaire, M. (2021). Capturing trade-offs between daily scheduling choices. Technical report TRANSP-OR 210101. )
\item[Xie et al., 2021]
Xie, S., Hillel, T., and Jin, Y. (2021). An Early Stopping Bayesian Data Assimilation Approach for Mixed-Logit Estimation. Technical report arXiv:2101.11159. )
\item[Rezvany et al., 2021]
Rezvany, N., Hillel, T., and Bierlaire, M. (2021). Integrated models of transport and energy demand: A literature review and framework. Technical report . )
\item[Ortelli et al., 2020]
Ortelli, N., Hillel, T., Pereira, F. C., de Lapparent, M., and Bierlaire, M. (2020). Assisted Specification of Discrete Choice Models. Technical report TRANSP-OR 200708. )
\item[Hillel, 2020]
Hillel, T. (2020). New perspectives on the performance of machine learning classifiers for mode-choice prediction. Technical report TRANSP-OR 200704. )
\item[Lederrey et al., 2019]
Lederrey, G., Lurkin, V., Hillel, T., and Bierlaire, M. (2019). Estimation of Discrete Choice Models with Hybrid Stochastic Adaptive Batch Size Algorithms. Technical report TRANSP-OR 191213. )
\item[Hillel et al., 2019]
Hillel, T., Bierlaire, M., and Jin, Y. (2019). A systematic review of machine learning methodologies for modelling passenger mode choice. Technical report TRANSP-OR 191025. )
