S. Vogt

发表

Evaluation of Anomaly Detection of an Autoencoder Based on Maintenace Information and Scada-Data

Marc-Alexander Lutz, S. Vogt, V. Berkhout, 2020 .

MAP D‐PHASE: real‐time demonstration of hydrological ensemble prediction systems

S. Vogt, U. Germann, M. Zappa, 2008 .

Application of numerical weather prediction in wind power forecasting: Assessment of the diurnal cycle

Stephan Vogt, Tobias Heppelmann, S. Vogt, 2017 .

Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning

S. Vogt, B. Sick, D. Kottke, 2022, ArXiv.

Uncertainty and Utility Sampling with Pre-Clustering

S. Vogt, B. Sick, Yujiang He, 2021, IAL@PKDD/ECML.

MAP D-PHASE: Demonstrating forecast capabilities for flood events in the Alpine region.

Volker Wulfmeyer, Andreas Behrendt, Silvio Davolio, 2009 .

Quantile Surfaces - Generalizing Quantile Regression to Multivariate Targets pdf

Bernhard Sick, Maarten Bieshaar, Stephan Vogt, 2020, ArXiv.

Targeted Adversarial Attacks on Wind Power Forecasts

S. Vogt, Malte Lehna, Christoph Scholz, 2023, ArXiv.

A review of uncertainty representations and metaverification of uncertainty assessment techniques for renewable energies

Bernhard Sick, Stephan Vogt, Andre Gensler, 2018, Renewable and Sustainable Energy Reviews.

Bayesian parameterisation of a regional photovoltaic model – Application to forecasting

Yves-Marie Saint-Drenan, Roland Potthast, Jamie M. Bright, 2019, Solar Energy.

An empirical approach to parameterizing photovoltaic plants for power forecasting and simulation

Yves-Marie Saint-Drenan, S. Bofinger, Rafael Fritz, 2015 .

Targeted Adversarial Attacks on Wind Power Forecasts

S. Vogt, Malte Lehna, Christoph Scholz, 2023, Machine Learning.

Power flow forecasts at transmission grid nodes using Graph Neural Networks

S. Vogt, J. M. Thomas, Clara Holzhüter, 2023, Energy and AI.