Nicole Ludwig - RankMe

33 papers Journal 20Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Assessing the risk of future Dunkelflaute events for Germany using generative deep learning. CoRR Felix Strnad, Jonathan Schmidt, Fabian Mockert, Philipp Hennig, Nicole Ludwig
2025	J	`jnl`	Bounded Graph Clustering with Graph Neural Networks. CoRR Kibidi Neocosmos, Diego Baptista, Nicole Ludwig
2025	J	`jnl`	Evaluating Weather Forecasts from a Decision Maker's Perspective. CoRR Kornelius Raeth, Nicole Ludwig
2025	J	`jnl`	Fault Detection in Solar Thermal Systems using Probabilistic Reconstructions. CoRR Florian Ebmeier, Nicole Ludwig, Jannik Thümmel, Georg Martius, Volker H. Franz
2025	J	`jnl`	RainShift: A Benchmark for Precipitation Downscaling Across Geographies. CoRR Paula Harder, Luca Schmidt, Francis Pelletier, Nicole Ludwig, Matthew Chantry, Christian Lessig, Alex Hernández-García, David Rolnick
2024	—	`conf`	PaSTS An Operational Dataset for Domestic Solar Thermal Systems. e-Energy Florian Ebmeier, Nicole Ludwig, Georg Martius, Volker H. Franz
2024	J	`jnl`	Spatiotemporally Coherent Probabilistic Generation of Weather from Climate. CoRR Jonathan Schmidt, Luca Schmidt, Felix Strnad, Nicole Ludwig, Philipp Hennig
2024	J	`jnl`	Towards turbine-location-aware multi-decadal wind power predictions with CMIP6. CoRR Nina Effenberger, Nicole Ludwig
2023	J	`jnl`	Inductive biases in deep learning models for weather prediction. CoRR Jannik Thümmel, Matthias Karlbauer, Sebastian Otte, Christiane Zarfl, Georg Martius, Nicole Ludwig, Thomas Scholten, Ulrich Friedrich, Volker Wulfmeyer, Bedartha Goswami, Martin V. Butz
2023	J	`jnl`	Probabilistic load forecasting using post-processed weather ensemble predictions. J. Oper. Res. Soc. Nicole Ludwig, Siddharth Arora, James W. Taylor
2023	J	`jnl`	Using weather data in energy time series forecasting: the benefit of input data transformations. Energy Inform. Oliver Neumann, Marian Turowski, Ralf Mikut, Veit Hagenmeyer, Nicole Ludwig
2022	J	`jnl`	A Collection and Categorization of Open-Source Wind and Wind Power Datasets. CoRR Nina Effenberger, Nicole Ludwig
2022	—	`conf`	Adaptively coping with concept drifts in energy time series forecasting using profiles. e-Energy Benedikt Heidrich, Nicole Ludwig, Marian Turowski, Ralf Mikut, Veit Hagenmeyer
2022	J	`jnl`	Analytical Uncertainty Propagation for Multi-Period Stochastic Optimal Power Flow. CoRR Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig, Veit Hagenmeyer
2022	J	`jnl`	Analytical Uncertainty Propagation for Multi-Period Stochastic Optimal Power Flow. CoRR Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig, Veit Hagenmeyer
2022	—	`conf`	Analytical uncertainty propagation and storage usage in a high RES Turkish transmission grid scenario. e-Energy Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig, Veit Hagenmeyer
2022	J	`jnl`	Net load forecasting using different aggregation levels. Energy Inform. Maximilian Beichter, Kaleb Phipps, Martha Maria Frysztacki, Ralf Mikut, Veit Hagenmeyer, Nicole Ludwig
2022	J	`jnl`	Sizing of Hybrid Energy Storage Systems Using Recurring Daily Patterns. IEEE Trans. Smart Grid Shahab Karrari, Nicole Ludwig, Giovanni De Carne, Mathias Noe
2021	—	`conf`	KIU-2021 Keynote: Uncertainty in Machine Learning for Environmental Research. GI-Jahrestagung Nicole Ludwig
2021	J	`jnl`	Smart Data Representations: Impact on the Accuracy of Deep Neural Networks. CoRR Oliver Neumann, Nicole Ludwig, Marian Turowski, Benedikt Heidrich, Veit Hagenmeyer, Ralf Mikut
2021	J	`jnl`	pyWATTS: Python Workflow Automation Tool for Time Series. CoRR Benedikt Heidrich, Andreas Bartschat, Marian Turowski, Oliver Neumann, Kaleb Phipps, Stefan Meisenbacher, Kai Schmieder, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer
2020	—	`—`	Data-Driven Methods for Demand-Side Flexibility in Energy Systems Nicole Ludwig
2020	—	`conf`	Forecasting energy time series with profile neural networks. e-Energy Benedikt Heidrich, Marian Turowski, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer
2019	—	`conf`	Industrial Demand-Side Flexibility: A Benchmark Data Set. e-Energy Nicole Ludwig, Lukas Barth, Dorothea Wagner, Veit Hagenmeyer
2018	J	`jnl`	A comprehensive modelling framework for demand side flexibility in smart grids. Comput. Sci. Res. Dev. Lukas Barth, Nicole Ludwig, Esther Mengelkamp, Philipp Staudt
2018	—	`conf`	Assessment of Unsupervised Standard Pattern Recognition Methods for Industrial Energy Time Series. e-Energy Nicole Ludwig, Simon Waczowicz, Ralf Mikut, Veit Hagenmeyer
2018	J	`jnl`	Concept and benchmark results for Big Data energy forecasting based on Apache Spark. J. Big Data Jorge Ángel González Ordiano, Andreas Bartschat, Nicole Ludwig, Eric Braun, Simon Waczowicz, Nicolas Renkamp, Nico Peter, Clemens Düpmeier, Ralf Mikut, Veit Hagenmeyer
2018	—	`conf`	Demand Response clustering: Automatically finding optimal cluster hyper-parameter values. e-Energy Simon Waczowicz, Nicole Ludwig, Jorge Ángel González Ordiano, Ralf Mikut, Veit Hagenmeyer
2018	—	`conf`	How much demand side flexibility do we need?: Analyzing where to exploit flexibility in industrial processes. e-Energy Lukas Barth, Veit Hagenmeyer, Nicole Ludwig, Dorothea Wagner
2018	—	`conf`	SCiBER: A new public data set of municipal building consumption. e-Energy Philipp Staudt, Nicole Ludwig, Julian Huber, Veit Hagenmeyer, Christof Weinhardt
2017	—	`conf`	Towards coding strategies for forecasting-based scheduling in smart grids and the energy lab 2.0. GECCO (Companion) Wilfried Jakob, Jorge Ángel González Ordiano, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer
2016	—	`conf`	Time Series Analysis for Big Data: Evaluating Bayesian Structural Time Series using Electricity Prices. MKWI Nicole Ludwig, Stefan Feuerriegel, Dirk Neumann
2015	J	`jnl`	Putting Big Data analytics to work: Feature selection for forecasting electricity prices using the LASSO and random forests. J. Decis. Syst. Nicole Ludwig, Stefan Feuerriegel, Dirk Neumann