Putting Big Data analytics to work: Feature selection for forecasting electricity prices using the LASSO and random forests. - Nicole Ludwig 002; Stefan Feuerriegel; Dirk Neumann 001 (J. Decis. Syst., 2015)

Time Series Analysis for Big Data: Evaluating Bayesian Structural Time Series using Electricity Prices. - Nicole Ludwig 002; Stefan Feuerriegel; Dirk Neumann 001 (MKWI, 2016)

Towards coding strategies for forecasting-based scheduling in smart grids and the energy lab 2.0. - Wilfried Jakob; Jorge Ángel González Ordiano; Nicole Ludwig 002; Ralf Mikut; Veit Hagenmeyer (GECCO (Companion), 2017)

Assessment of Unsupervised Standard Pattern Recognition Methods for Industrial Energy Time Series. - Nicole Ludwig 002; Simon Waczowicz; Ralf Mikut; Veit Hagenmeyer (e-Energy, 2018)

How much demand side flexibility do we need?: Analyzing where to exploit flexibility in industrial processes. - Lukas Barth; Veit Hagenmeyer; Nicole Ludwig 002; Dorothea Wagner (e-Energy, 2018)

SCiBER: A new public data set of municipal building consumption. - Philipp Staudt; Nicole Ludwig 002; Julian Huber; Veit Hagenmeyer; Christof Weinhardt (e-Energy, 2018)

Demand Response clustering: Automatically finding optimal cluster hyper-parameter values. - Simon Waczowicz; Nicole Ludwig 002; Jorge Ángel González Ordiano; Ralf Mikut; Veit Hagenmeyer (e-Energy, 2018)

A comprehensive modelling framework for demand side flexibility in smart grids. - Lukas Barth; Nicole Ludwig 002; Esther Mengelkamp; Philipp Staudt (Comput. Sci. Res. Dev., 2018)

Concept and benchmark results for Big Data energy forecasting based on Apache Spark. - Jorge Ángel González Ordiano; Andreas Bartschat; Nicole Ludwig 002; Eric Braun; Simon Waczowicz; Nicolas Renkamp; Nico Peter; Clemens Düpmeier; Ralf Mikut; Veit Hagenmeyer (J. Big Data, 2018)

Industrial Demand-Side Flexibility: A Benchmark Data Set. - Nicole Ludwig 002; Lukas Barth; Dorothea Wagner; Veit Hagenmeyer (e-Energy, 2019)

Forecasting energy time series with profile neural networks. - Benedikt Heidrich; Marian Turowski; Nicole Ludwig 002; Ralf Mikut; Veit Hagenmeyer (e-Energy, 2020)

Data-Driven Methods for Demand-Side Flexibility in Energy Systems - Nicole Ludwig 002 (2020)

KIU-2021 Keynote: Uncertainty in Machine Learning for Environmental Research. - Nicole Ludwig 002 (GI-Jahrestagung, 2021)

pyWATTS: Python Workflow Automation Tool for Time Series. - Benedikt Heidrich; Andreas Bartschat; Marian Turowski; Oliver Neumann; Kaleb Phipps; Stefan Meisenbacher; Kai Schmieder; Nicole Ludwig 002; Ralf Mikut; Veit Hagenmeyer (CoRR, 2021)

Smart Data Representations: Impact on the Accuracy of Deep Neural Networks. - Oliver Neumann; Nicole Ludwig 002; Marian Turowski; Benedikt Heidrich; Veit Hagenmeyer; Ralf Mikut (CoRR, 2021)

Analytical uncertainty propagation and storage usage in a high RES Turkish transmission grid scenario. - Rebecca Bauer; Tillmann Mühlpfordt; Nicole Ludwig 002; Veit Hagenmeyer (e-Energy, 2022)

Adaptively coping with concept drifts in energy time series forecasting using profiles. - Benedikt Heidrich; Nicole Ludwig 002; Marian Turowski; Ralf Mikut; Veit Hagenmeyer (e-Energy, 2022)

A Collection and Categorization of Open-Source Wind and Wind Power Datasets. - Nina Effenberger; Nicole Ludwig 002 (CoRR, 2022)

Analytical Uncertainty Propagation for Multi-Period Stochastic Optimal Power Flow. - Rebecca Bauer; Tillmann Mühlpfordt; Nicole Ludwig 002; Veit Hagenmeyer (CoRR, 2022)

Net load forecasting using different aggregation levels. - Maximilian Beichter; Kaleb Phipps; Martha Maria Frysztacki; Ralf Mikut; Veit Hagenmeyer; Nicole Ludwig 002 (Energy Inform., 2022)

Sizing of Hybrid Energy Storage Systems Using Recurring Daily Patterns. - Shahab Karrari; Nicole Ludwig 002; Giovanni De Carne; Mathias Noe (IEEE Trans. Smart Grid, 2022)

Inductive biases in deep learning models for weather prediction. - Jannik Thümmel; Matthias Karlbauer; Sebastian Otte; Christiane Zarfl; Georg Martius; Nicole Ludwig 002; Thomas Scholten; Ulrich Friedrich; Volker Wulfmeyer; Bedartha Goswami; Martin V. Butz (CoRR, 2023)

Using weather data in energy time series forecasting: the benefit of input data transformations. - Oliver Neumann; Marian Turowski; Ralf Mikut; Veit Hagenmeyer; Nicole Ludwig 002 (Energy Inform., 2023)

Probabilistic load forecasting using post-processed weather ensemble predictions. - Nicole Ludwig 002; Siddharth Arora; James W. Taylor (J. Oper. Res. Soc., 2023)

PaSTS An Operational Dataset for Domestic Solar Thermal Systems. - Florian Ebmeier; Nicole Ludwig 002; Georg Martius; Volker H. Franz (e-Energy, 2024)

Towards turbine-location-aware multi-decadal wind power predictions with CMIP6. - Nina Effenberger; Nicole Ludwig 002 (CoRR, 2024)

Spatiotemporally Coherent Probabilistic Generation of Weather from Climate. - Jonathan Schmidt 001; Luca Schmidt; Felix Strnad; Nicole Ludwig 002; Philipp Hennig (CoRR, 2024)

RainShift: A Benchmark for Precipitation Downscaling Across Geographies. - Paula Harder; Luca Schmidt; Francis Pelletier; Nicole Ludwig 002; Matthew Chantry; Christian Lessig; Alex Hernández-García; David Rolnick (CoRR, 2025)