4 citations · 12 across the 6 of their papers we have counts for
5 papers · 1 filter
Deep Evidential Learning for Bayesian Quantile Regression
Frederik Boe Hüttel, Filipe Rodrigues, Francisco Câmara Pereira
It is desirable to have accurate uncertainty estimation from a single deterministic forward-pass model, as traditional methods for uncertainty quantification are computationally ex…
Analyzing the Reporting Error of Public Transport Trips in the Danish National Travel Survey Using Smart Card Data
Georges Sfeir, Filipe Rodrigues, Maya Abou Zeid +1
Household travel surveys have been used for decades to collect individuals and households' travel behavior. However, self-reported surveys are subject to recall bias, as respondent…
Railway Network Delay Evolution: A Heterogeneous Graph Neural Network Approach
Zhongcan Li, Ping Huang, Chao Wen +1
Railway operations involve different types of entities (stations, trains, etc.), making the existing graph/network models with homogenous nodes (i.e., the same kind of nodes) incap…
Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning
Carolin Schmidt, Daniele Gammelli, Francisco Camara Pereira +1
Autonomous Mobility-on-Demand (AMoD) systems are an evolving mode of transportation in which a centrally coordinated fleet of self-driving vehicles dynamically serves travel reques…
Mind the Gap: Modelling Difference Between Censored and Uncensored Electric Vehicle Charging Demand
Frederik Boe Hüttel, Filipe Rodrigues, Francisco Câmara Pereira
Electric vehicle charging demand models, with charging records as input, will inherently be biased toward the supply of available chargers. These models often fail to account for d…