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20242026
most citedSpatio-Temporal Graph Neural Network for Urban Spaces: Interpolating Citywide Traffic Volume

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Hierarchical Forecast Reconciliation for Urban Rail Transit Demand Prediction under Operational Disruptions

Dang Viet Anh Nguyen, Alma Fazlagic, Kristine Pryds Loft +1

Accurate and coherent passenger demand forecasting is essential for Urban Rail Transit (URT) operations. Passenger demand has a hierarchical structure in which origin-destination (…

cs.LG2026

Time Series Foundation Models as Strong Baselines in Transportation Forecasting: A Large-Scale Benchmark Analysis

Javier Yanes-Pulido, Filipe Rodrigues

Accurate forecasting of transportation dynamics is essential for urban mobility and infrastructure planning. Although recent work has achieved strong performance with deep learning…

cs.LG2025★ 1 cited

Robustness of Reinforcement Learning-Based Traffic Signal Control under Incidents: A Comparative Study

Dang Viet Anh Nguyen, Carlos Lima Azevedo, Tomer Toledo +1

Reinforcement learning-based traffic signal control (RL-TSC) has emerged as a promising approach for improving urban mobility. However, its robustness under real-world disruptions…

cs.LG2025★ 1 cited

Spatio-Temporal Graph Neural Network for Urban Spaces: Interpolating Citywide Traffic Volume

Silke K. Kaiser, Filipe Rodrigues, Carlos Lima Azevedo +1

Graph Neural Networks have shown strong performance in traffic volume forecasting, particularly on highways and major arterial networks. Applying them to urban settings, however, p…

cs.LG2025

Deep Reinforcement Learning for Day-to-day Dynamic Tolling in Tradable Credit Schemes

Xiaoyi Wu, Ravi Seshadri, Filipe Rodrigues +1

Tradable credit schemes (TCS) are an increasingly studied alternative to congestion pricing, given their revenue neutrality and ability to address issues of equity through the init…

physics.soc-ph2025

Choice Sets and Smart Card Data In Public Transport Route Choice Models: Generated vs. Empirical Sets

Georges Sfeir, Filipe Rodrigues, Ravi Seshadri +1

This study evaluates path sets generation for route choice models in multimodal public transportation networks, using both conventional (network algorithms) and empirical (smart ca…