5 citations · 9 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 5 cited
Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time-Series Forecast
Jens Schreiber, Stephan Vogt, Bernhard Sick
Task embeddings in multi-layer perceptrons for multi-task learning and inductive transfer learning in renewable power forecasts have recently been introduced. In many cases, this a…
cs.LG2022★ 4 cited
Synthetic Photovoltaic and Wind Power Forecasting Data
Stephan Vogt, Jens Schreiber, Bernhard Sick
Photovoltaic and wind power forecasts in power systems with a high share of renewable energy are essential in several applications. These include stable grid operation, profitable…
stat.AP2020
Quantile Surfaces -- Generalizing Quantile Regression to Multivariate Targets
Maarten Bieshaar, Jens Schreiber, Stephan Vogt +2
In this article, we present a novel approach to multivariate probabilistic forecasting. Our approach is based on an extension of single-output quantile regression (QR) to multivari…