An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles. - Niklas Åkerblom; Yuxin Chen 001; Morteza Haghir Chehreghani (IJCAI, 2020)

Passive and Active Learning of Driver Behavior from Electric Vehicles. - Federica Comuni; Christopher Mészáros; Niklas Åkerblom; Morteza Haghir Chehreghani (ITSC, 2022)

An Online Learning Approach for Vehicle Usage Prediction During COVID-19. - Tobias Lindroth; Axel Svensson; Niklas Åkerblom; Mitra Pourabdollah; Morteza Haghir Chehreghani (CoRR, 2022)

Combinatorial Gaussian Process Bandits in Bayesian Settings: Theory and Application for Energy-Efficient Navigation. - Jack Sandberg; Niklas Åkerblom; Morteza Haghir Chehreghani (CoRR, 2023)

A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles. - Niklas Åkerblom; Morteza Haghir Chehreghani (Trans. Mach. Learn. Res., 2023)

Online learning of network bottlenecks via minimax paths. - Niklas Åkerblom; Fazeleh Sadat Hoseini; Morteza Haghir Chehreghani (Mach. Learn., 2023)

Online learning of energy consumption for navigation of electric vehicles. - Niklas Åkerblom; Yuxin Chen 001; Morteza Haghir Chehreghani (Artif. Intell., 2023)

A Contextual Combinatorial Semi-Bandit Approach to Network Bottleneck Identification. - Fazeleh Sadat Hoseini; Niklas Åkerblom; Morteza Haghir Chehreghani (CIKM, 2024)

Tree Ensembles for Contextual Bandits. - Hannes Nilsson; Rikard Johansson; Niklas Åkerblom; Morteza Haghir Chehreghani (Trans. Mach. Learn. Res., 2024)

Online Learning Models for Vehicle Usage Prediction During COVID-19. - Tobias Lindroth; Axel Svensson; Niklas Åkerblom; Mitra Pourabdollah; Morteza Haghir Chehreghani (IEEE Trans. Intell. Transp. Syst., 2024)

Bayesian Analysis of Combinatorial Gaussian Process Bandits. - Jack Sandberg; Niklas Åkerblom; Morteza Haghir Chehreghani (ICLR, 2025)

Cost-Efficient Online Decision Making: A Combinatorial Multi-Armed Bandit Approach. - Arman Rahbar; Niklas Åkerblom; Morteza Haghir Chehreghani (Trans. Mach. Learn. Res., 2025)