Jens Schreiber
Jens Schreiber
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Generative adversarial networks for operational scenario planning of renewable energy farms: A study on wind and photovoltaic
J Schreiber, M Jessulat, B Sick
International Conference on Artificial Neural Networks, 550-564, 2019
Quantifying the influences on probabilistic wind power forecasts
J Schreiber, B Sick
arXiv preprint arXiv:1808.04750, 2018
Influences in forecast errors for wind and photovoltaic power: a study on machine learning models
J Schreiber, A Buschin, B Sick
arXiv preprint arXiv:1905.13668, 2019
Representation Learning in Power Time Series Forecasting
J Henze, J Schreiber, B Sick
Deep Learning: Algorithms and Applications, 67-101, 2020
A Transfer Learning Framework Providing Power Forecasts Throughout the Lifecycle of Wind Farms After Initial Connection to the Electrical Grid
J Schreiber
Organic Computing: Doctoral Dissertation Colloquium 2018 13, 75, 2019
Carpe noctem 2009
T Amma, P Baer, K Baumgart, P Burghardt, K Geihs, J Henze, S Opfer, ...
RoboCup 2009 International Symposium. TU Graz, Graz, 2009
Emerging Relation Network and Task Embedding for Multi-Task Regression Problems
J Schreiber, B Sick
2020 25th International Conference on Pattern Recognition (ICPR), 2663-2670, 2021
Quantile Surfaces--Generalizing Quantile Regression to Multivariate Targets
M Bieshaar, J Schreiber, S Vogt, A Gensler, B Sick
arXiv preprint arXiv:2010.05898, 2020
Coopetitive Soft Gating Ensemble
S Deist, M Bieshaar, J Schreiber, A Gensler, B Sick
arXiv preprint arXiv:1807.01020, 2018
Extended Coopetitive Soft Gating Ensemble
S Deist, J Schreiber, M Bieshaar, B Sick
arXiv preprint arXiv:2004.14026, 2020
Coopetitive Soft Gating Ensemble
J Schreiber, M Bieshaar, A Gensler, B Sick, S Deist
2018 IEEE 3rd International Workshops on Foundations and Applications of …, 2018
Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time Series Forecast
J Schreiber, S Vogt, B Sick
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021
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