Tim Hillel

According to our database, Tim Hillel authored at least 9 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

ParamBoost: Gradient Boosted Piecewise Cubic Polynomials.

Nicolas Salvadé, Tim Hillel

CoRR, April, 2026

2025

ActVAE: Modelling human activity schedules with a deep conditional generative approach.

Fred Shone, Tim Hillel

CoRR, December, 2025

Functional effects models: Accounting for preference heterogeneity in panel data with machine learning.

Nicolas Salvadé, Tim Hillel

CoRR, September, 2025

Modelling Activity Scheduling Behaviour with Deep Generative Machine Learning.

Fred Shone, Tim Hillel

CoRR, January, 2025

2024

RUMBoost: Gradient Boosted Random Utility Models.

Nicolas Salvadé, Tim Hillel

CoRR, 2024

2023

A prediction and behavioural analysis of machine learning methods for modelling travel mode choice.

José Ángel Martín-Baos, Julio Alberto López-Gómez, Luis Rodriguez-Benitez, Tim Hillel, Ricardo García-Ródenas

CoRR, 2023

2022

ciDATGAN: Conditional Inputs for Tabular GANs.

Gael Lederrey, Tim Hillel, Michel Bierlaire

CoRR, 2022

DATGAN: Integrating expert knowledge into deep learning for synthetic tabular data.

Gael Lederrey, Tim Hillel, Michel Bierlaire

CoRR, 2022

2021

An Early Stopping Bayesian Data Assimilation Approach for Mixed-Logit Estimation.

Shanshan Xie, Tim Hillel, Ying Jin

CoRR, 2021