Frederik Boe Hüttel

According to our database, Frederik Boe Hüttel authored at least 8 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Using mobile charging stations as probes to discover latent EV charging demand in stochastic environments: A deep reinforcement learning approach.

Atefeh Hemmati Golsefidi, Frederik Boe Hüttel, Samitha Samaranayake, Francisco Câmara Pereira

Expert Syst. Appl., 2026

2025

Bayesian Active Learning for Censored Regression.

Frederik Boe Hüttel, Christoffer Riis, Filipe Rodrigues, Francisco C. Pereira

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

2023

Deep Evidential Learning for Bayesian Quantile Regression.

Frederik Boe Hüttel, Filipe Rodrigues, Francisco Câmara Pereira

CoRR, 2023

Mind the Gap - Modelling Difference Between Censored and Uncensored Electric Vehicle Charging Demand.

Frederik Boe Hüttel, Filipe Rodrigues, Francisco Câmara Pereira

CoRR, 2023

2022

Modeling Censored Mobility Demand Through Censored Quantile Regression Neural Networks.

Frederik Boe Hüttel, Inon Peled, Filipe Rodrigues, Francisco C. Pereira

IEEE Trans. Intell. Transp. Syst., 2022

Bayesian Active Learning with Fully Bayesian Gaussian Processes.

Christoffer Riis, Francisco Antunes, Frederik Boe Hüttel, Carlos Lima Azevedo, Francisco Pereira

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Deep Spatio-Temporal Forecasting of Electrical Vehicle Charging Demand.

Frederik Boe Hüttel, Inon Peled, Filipe Rodrigues, Francisco C. Pereira

CoRR, 2021

Consistent and accurate estimation of stellar parameters from HARPS-N Spectroscopy using Deep Learning.

Frederik Boe Hüttel, Line Katrine Harder Clemmensen

Proceedings of the 2021 Northern Lights Deep Learning Workshop, 2021