Time-adaptive quantile regression. - Jan Kloppenborg Møller; Henrik Aalborg Nielsen; Henrik Madsen (Comput. Stat. Data Anal., 2008)

Inhomogeneous Markov Models for Describing Driving Patterns. - Emil Banning Iversen; Jan Kloppenborg Møller; Juan Miguel Morales 001; Henrik Madsen (IEEE Trans. Smart Grid, 2017)

Behind-the-Meter Energy Flexibility Modelling for Aggregator Operation with a Focus on Uncertainty. - Emma M. V. Blomgren; Razgar Ebrahimy; Ali Pourmousavi Kani; Jan Kloppenborg Møller; Francesco D'Ettorre; Mohsen Banaei; Henrik Madsen (ISGT-Europe, 2021)

Hierarchical learning, forecasting coherent spatio-temporal individual and aggregated building loads. - Julien Leprince; Henrik Madsen; Jan Kloppenborg Møller; Wim Zeiler (CoRR, 2023)

Structural hierarchical learning for energy networks. - Julien Leprince; Waqas Khan; Henrik Madsen; Jan Kloppenborg Møller; Wim Zeiler (CoRR, 2023)

A step towards digital operations - A novel grey-box approach for modelling the heat dynamics of Ultra-low temperature freezing chambers. - Tao Huang; Peder Bacher; Jan Kloppenborg Møller; Francesco D'Ettorre; Wiebke Brix Markussen (CoRR, 2023)

Onlineforecast: An R Package for Adaptive and Recursive Forecasting. - Peder Bacher; Hjörleifur G. Bergsteinsson; Linde Frölke; Mikkel L. Sørensen; Julián Lemos-Vinasco; Jon A. R. Liisberg; Jan Kloppenborg Møller; Henrik Aalborg Nielsen; Henrik Madsen (R J., 2023)

Sequential methods for error correction of probabilistic wind power forecasts. - Bastian Schmidt Jørgensen; Jan Kloppenborg Møller; Peter Nystrup; Henrik Madsen (Expert Syst. Appl., 2025)

A covariate-dependent Markov jump process with application to the propagation of rail defect severity. - Albert Skovgaard Bisgaard; Steven Harrod; Jan Kloppenborg Møller; Bo Friis Nielsen; Carsten Jørn Rasmussen; Thomas Vatn Bjørge; Jørn Vatn (Reliab. Eng. Syst. Saf., 2025)

nabqr: Python package for correcting probabilistic forecasts. - Bastian Schmidt Jørgensen; Jan Kloppenborg Møller; Peter Nystrup; Henrik Madsen (SoftwareX, 2025)

nabqr: Python package for improving probabilistic forecasts. - Bastian Schmidt Jørgensena; Jan Kloppenborg Møller; Peter Nystrup; Henrik Madsen (CoRR, 2025)