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Frederik Boe Hüttel
Frederik Boe Hüttel
Other namesFrederik Boe Huttel
Verified email at dtu.dk
Title
Cited by
Cited by
Year
Bayesian active learning with fully bayesian gaussian processes
C Riis, F Antunes, F Hüttel, C Lima Azevedo, F Pereira
Advances in Neural Information Processing Systems 35, 12141-12153, 2022
162022
Deep spatio-temporal forecasting of electrical vehicle charging demand
FB Hüttel, I Peled, F Rodrigues, FC Pereira
arXiv preprint arXiv:2106.10940, 2021
162021
Modeling censored mobility demand through censored quantile regression neural networks
FB Hüttel, I Peled, F Rodrigues, FC Pereira
IEEE Transactions on Intelligent Transportation Systems 23 (11), 21753-21765, 2022
72022
Analysis of social interactions and risk factors relevant to the spread of infectious diseases at hospitals and nursing homes
FB Hüttel, AM Iversen, M Bo Hansen, B Kjær Ersbøll, S Ellermann-Eriksen, ...
Plos one 16 (9), e0257684, 2021
42021
Computer vision-based helmet use registration for e-scooter riders–The impact of the mandatory helmet law in Copenhagen
FW Siebert, C Riis, KH Janstrup, H Lin, FB Hüttel
Journal of safety research 87, 257-265, 2023
32023
Mind the gap: Modelling difference between censored and uncensored electric vehicle charging demand
FB Hüttel, F Rodrigues, FC Pereira
Transportation Research Part C: Emerging Technologies 153, 104189, 2023
22023
A joint machine learning and optimization approach for incremental expansion of electric vehicle charging infrastructure
AH Golsefidi, FB Hüttel, I Peled, S Samaranayake, FC Pereira
Transportation Research Part A: Policy and Practice 178, 103863, 2023
12023
Deep Evidential Learning for Bayesian Quantile Regression
FB Hüttel, F Rodrigues, FC Pereira
arXiv preprint arXiv:2308.10650, 2023
12023
Automated detection of bicycle helmets using deep learning
FW Siebert, C Riis, KH Janstrup, H Lin, J Kristensen, O Gül, FB Hüttel
Journal of Cycling and Micromobility Research 2, 100013, 2024
2024
Bayesian Active Learning for Censored Regression
FB Hüttel, C Riis, F Rodrigues, FC Pereira
arXiv preprint arXiv:2402.11973, 2024
2024
Consistent and accurate estimation of stellar parameters from HARPS-N Spectroscopy using Deep Learning
FB Hüttel, LKH Clemmensen
Proceedings of the Northern Lights Deep Learning Workshop 2, 2021
2021
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Articles 1–11