Michael Steininger

Publication Activity (10 Years)

Years Active: 2020-2023
Publications (10 Years): 21

Top Topics

Anomaly Detection

Supervised Learning

Water Distribution Networks

Top Venues

Publications

Melanie Schaller, Michael Steininger, Andrzej Dulny, Daniel Schlör, Andreas Hotho
Liquor-HGNN: A heterogeneous graph neural network for leakage detection in water distribution networks. LWDA (2023)
Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho
ConvMOS: climate model output statistics with deep learning. Data Min. Knowl. Discov. 37 (1) (2023)
Lucas Wittstruck, Heike Gerighausen, Annelie Säurich, Markus Möller, Knut Hartmann, Michael Steininger, Simone Zepp, Thomas Jarmer
Räumliche Erfassung des organischen Kohlenstoffgehaltes von Böden einer landwirtschaftlichen Intensivregion aus Sentinel-2-Daten. GIL Jahrestagung (2023)
Konstantin Kobs, Michael Steininger, Andreas Hotho
InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images. WACV (2023)
Padraig Davidson, Michael Steininger, André Huhn, Anna Krause, Andreas Hotho
Semi-unsupervised Learning for Time Series Classification. CoRR (2022)
Konstantin Kobs, Michael Steininger, Andreas Hotho
InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images. CoRR (2022)
Konstantin Kobs, Michael Steininger, Andrzej Dulny, Andreas Hotho
Do Different Deep Metric Learning Losses Lead to Similar Learned Features? CoRR (2022)
Konstantin Kobs, Michael Steininger, Andrzej Dulny, Andreas Hotho
Do Different Deep Metric Learning Losses Lead to Similar Learned Features? ICCV (2021)
Simone Zepp, Uta Heiden, Martin Bachmann, Martin Wiesmeier, Michael Steininger, Bas van Wesemael
Estimation of Soil Organic Carbon Contents in Croplands of Bavaria from SCMaP Soil Reflectance Composites. Remote. Sens. 13 (16) (2021)
Pascal Janetzky, Padraig Davidson, Michael Steininger, Anna Krause, Andreas Hotho
Detecting Presence Of Speech In Acoustic Data Obtained From Beehives. DCASE (2021)
Padraig Davidson, Florian Buckermann, Michael Steininger, Anna Krause, Andreas Hotho
Semi-unsupervised Learning: An In-depth Parameter Analysis. KI (2021)
Padraig Davidson, Michael Steininger, Florian Lautenschlager, Anna Krause, Andreas Hotho
Anomaly Detection in Beehives: An Algorithm Comparison. CoRR (2021)
Michael Steininger, Konstantin Kobs, Padraig Davidson, Anna Krause, Andreas Hotho
Density-based weighting for imbalanced regression. Mach. Learn. 110 (8) (2021)
Padraig Davidson, Michael Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause, Andreas Hotho
Anomaly Detection in Beehives using Deep Recurrent Autoencoders. SENSORNETS (2020)
Michael Steininger, Konstantin Kobs, Albin Zehe, Florian Lautenschlager, Martin Becker, Andreas Hotho
MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images. ACM Trans. Spatial Algorithms Syst. 6 (3) (2020)
Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho
Deep Learning for Climate Model Output Statistics. CoRR (2020)
Konstantin Kobs, Michael Steininger, Albin Zehe, Florian Lautenschlager, Andreas Hotho
SimLoss: Class Similarities in Cross Entropy. ISMIS (2020)
Konstantin Kobs, Christian Schäfer, Michael Steininger, Anna Krause, Roland Baumhauer, Heiko Paeth, Andreas Hotho
Semi-Supervised Learning for Grain Size Distribution Interpolation. ICPR Workshops (6) (2020)
Padraig Davidson, Michael Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause, Andreas Hotho
Anomaly Detection in Beehives using Deep Recurrent Autoencoders. CoRR (2020)
Konstantin Kobs, Michael Steininger, Albin Zehe, Florian Lautenschlager, Andreas Hotho
SimLoss: Class Similarities in Cross Entropy. CoRR (2020)
Michael Steininger, Konstantin Kobs, Albin Zehe, Florian Lautenschlager, Martin Becker, Andreas Hotho
MapLUR: Exploring a new Paradigm for Estimating Air Pollution using Deep Learning on Map Images. CoRR (2020)