Short-Term Density Forecasting of Low-Voltage Load Using Bernstein-Polynomial Normalizing Flows. - Marcel Arpogaus; Marcus Voss; Beate Sick; Mark Nigge-Uricher; Oliver Dürr (IEEE Trans. Smart Grid, 2023)

How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression. - Lucas Kook; Chris Kolb; Philipp Schiele; Daniel Dold; Marcel Arpogaus; Cornelius Fritz; Philipp F. M. Baumann; Philipp Kopper; Tobias Pielok; Emilio Dorigatti; David Rügamer (UAI, 2024)

Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression with Interpretable Marginals. - Marcel Arpogaus; Thomas Kneib; Thomas Nagler; David Rügamer (UAI, 2025)

Time-series surrogates from energy consumers generated by machine learning approaches for long-term forecasting scenarios. - Ben Gerhards; Nikita Popkov; Annekatrin König; Marcel Arpogaus; Bastian Schäfermeier; Leonie Riedl; Stephan Vogt; Philip Hehlert (CoRR, 2025)