4 papers
GUIDED Network-Agnostic Feature Initialization for Spatial Transferability in GNN-based Models
Alessandro Scalese, Santhanakrishnan Narayanan, Constantinos Antoniou
The Traffic Assignment Problem is a fundamental but computationally expensive component of transportation planning. While Graph Neural Networks have emerged as fast, data-driven su…
LLMs on Tabular Data with Limited Semantics: Evidence from Industrial Car Retrofit Prediction
Aina Vila Pons, Ioannis Tzachristas, Constantinos Antoniou
Industrial retrofit planning depends on structured operational data rather than free text: planners must estimate whether a newly registered prototype will require a retrofit, whic…
Development of a graph neural network surrogate for travel demand modelling
Nikita Makarov, Santhanakrishnan Narayanan, Constantinos Antoniou
As urban environments grow, the modelling of transportation systems becomes increasingly complex. This paper advances the field of travel demand modelling by introducing advanced G…
Guided Persona-based AI Surveys: Can we replicate personal mobility preferences at scale using LLMs?
Ioannis Tzachristas, Santhanakrishnan Narayanan, Constantinos Antoniou
This study explores the potential of Large Language Models (LLMs) to generate artificial surveys, with a focus on personal mobility preferences in Germany. By leveraging LLMs for s…