Tomography of the London Underground: a Scalable Model for Origin-Destination Data

Nicolò Colombo, Ricardo Silva, Soong Moon Kang

Nov-21-2025, 12:29:01 GMT–Neural Information Processing Systems

Based on the reconstruction of the users' travel time distribution, the model is

artificial intelligence, bayesian inference, machine learning, (19 more...)

Neural Information Processing Systems

Nov-21-2025, 12:29:01 GMT

Conferences PDF

Country:
- Asia
  - China > Beijing
    - Beijing (0.04)
  - Singapore (0.04)
- Europe > United Kingdom
  - England
    - Cambridgeshire > Cambridge (0.04)
    - Greater London > London (0.41)
- North America > United States
  - California > Los Angeles County > Long Beach (0.04)

Industry:
- Transportation
  - Ground > Rail (1.00)
  - Passenger (1.00)

Technology:
- Information Technology
  - Artificial Intelligence
    - Machine Learning (1.00)
    - Representation & Reasoning
      - Agents (0.93)
      - Uncertainty > Bayesian Inference (0.47)
  - Communications > Networks (1.00)

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Tomography of the London Underground: a Scalable Model for Origin-Destination Data
Tomography of the London Underground: a Scalable Model for Origin-Destination Data

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