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08/21/2023
Deep Evidential Learning for Bayesian Quantile Regression
It is desirable to have accurate uncertainty estimation from a single de...
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08/02/2023
Analyzing the Reporting Error of Public Transport Trips in the Danish National Travel Survey Using Smart Card Data
Household travel surveys have been used for decades to collect individua...
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05/16/2023
Graph Reinforcement Learning for Network Control via Bi-Level Optimization
Optimization problems over dynamic networks have been extensively studie...
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03/27/2023
Railway Network Delay Evolution: A Heterogeneous Graph Neural Network Approach
Railway operations involve different types of entities (stations, trains...
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02/28/2023
Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning
Autonomous Mobility-on-Demand (AMoD) systems are a rapidly evolving mode...
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01/16/2023
Mind the Gap – Modelling Difference Between Censored and Uncensored Electric Vehicle Charging Demand
Electric vehicle charging demand models, with charging records as input,...
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10/11/2022
Context-aware Bayesian choice models
The mixed multinomial logit (MMNL) model assumes constant preference par...
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08/09/2022
Representation learning of rare temporal conditions for travel time prediction
Predicting travel time under rare temporal conditions (e.g., public holi...
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03/06/2022
On the importance of stationarity, strong baselines and benchmarks in transport prediction problems
Over the last years, the transportation community has witnessed a tremen...
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01/25/2022
Unboxing the graph: Neural Relational Inference for Mobility Prediction
Predicting the supply and demand of transport systems is vital for effic...
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07/28/2021
Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management
Bike-sharing systems are a rapidly developing mode of transportation and...
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06/21/2021
Deep Spatio-Temporal Forecasting of Electrical Vehicle Charging Demand
Electric vehicles can offer a low carbon emission solution to reverse ri...
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04/23/2021
Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems
Autonomous mobility-on-demand (AMoD) systems represent a rapidly develop...
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04/14/2021
Short-term bus travel time prediction for transfer synchronization with intelligent uncertainty handling
This paper presents two novel approaches for uncertainty estimation adap...
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04/02/2021
Modeling Censored Mobility Demand through Quantile Regression Neural Networks
Shared mobility services require accurate demand models for effective se...
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01/28/2021
Gaussian Process Latent Class Choice Models
We present a Gaussian Process - Latent Class Choice Model (GP-LCCM) to i...
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09/10/2020
Generalized Multi-Output Gaussian Process Censored Regression
When modelling censored observations, a typical approach in current regr...
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07/06/2020
Semi-nonparametric Latent Class Choice Model with a Flexible Class Membership Component: A Mixture Model Approach
This study presents a semi-nonparametric Latent Class Choice Model (LCCM...
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06/09/2020
Recurrent Flow Networks: A Recurrent Latent Variable Model for Spatio-Temporal Density Modelling
When modelling real-valued sequences, a typical approach in current RNN ...
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04/11/2020
Scaling Bayesian inference of mixed multinomial logit models to very large datasets
Variational inference methods have been shown to lead to significant imp...
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01/21/2020
Estimating Latent Demand of Shared Mobility through Censored Gaussian Processes
Transport demand is highly dependent on supply, especially for shared tr...
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06/10/2019
Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models
Specifying utility functions is a key step towards applying the discrete...
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04/17/2019
Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures
Reinforcement learning (RL) constitutes a promising solution for allevia...
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03/07/2019
Multi-output Bus Travel Time Prediction with Convolutional LSTM Neural Network
Accurate and reliable travel time predictions in public transport networ...
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12/20/2018
A Bayesian Additive Model for Understanding Public Transport Usage in Special Events
Public special events, like sports games, concerts and festivals are wel...
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12/20/2018
Multi-Output Gaussian Processes for Crowdsourced Traffic Data Imputation
Traffic speed data imputation is a fundamental challenge for data-driven...
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12/20/2018
Heteroscedastic Gaussian processes for uncertainty modeling in large-scale crowdsourced traffic data
Accurately modeling traffic speeds is a fundamental part of efficient in...
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08/27/2018
Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problems
Spatio-temporal problems are ubiquitous and of vital importance in many ...
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08/17/2018
Learning Supervised Topic Models for Classification and Regression from Crowds
The growing need to analyze large collections of documents has led to gr...
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08/16/2018
Combining time-series and textual data for taxi demand prediction in event areas: a deep learning approach
Accurate time-series forecasting is vital for numerous areas of applicat...
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09/06/2017