Synthesising activity participations and scheduling with deep generative machine learning

Fred Shone, Tim Hillel

Open source

DOI: 10.1016/j.trc.2025.105273
Published: 2025-10
Container: Transportation Research Part C: Emerging Technologies
Publisher: Elsevier BV
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1016/j.trc.2025.105273,
  title = {Synthesising activity participations and scheduling with deep generative machine learning},
  author = {Fred Shone and Tim Hillel},
  year = {2025},
  journal = {Transportation Research Part C: Emerging Technologies},
  doi = {10.1016/j.trc.2025.105273},
  url = {https://doi.org/10.1016/j.trc.2025.105273}
}

RIS

TY  - JOUR
TI  - Synthesising activity participations and scheduling with deep generative machine learning
AU  - Fred Shone
AU  - Tim Hillel
PY  - 2025
JO  - Transportation Research Part C: Emerging Technologies
DO  - 10.1016/j.trc.2025.105273
UR  - https://doi.org/10.1016/j.trc.2025.105273
ER  -

APA

Shone, F., & Hillel, T. (2025). Synthesising activity participations and scheduling with deep generative machine learning. Transportation Research Part C: Emerging Technologies. https://doi.org/10.1016/j.trc.2025.105273

Source records

crossref · retrieved 2026-09-25T19:40:10.518Z