| Density-based weighting for imbalanced regression M Steininger, K Kobs, P Davidson, A Krause, A Hotho Machine Learning 110 (8), 2187-2211, 2021 | 24 | 2021 |
| OpenLUR: Off-the-shelf air pollution modeling with open features and machine learning F Lautenschlager, M Becker, K Kobs, M Steininger, P Davidson, A Krause, ... Atmospheric Environment 233, 117535, 2020 | 17 | 2020 |
| Anomaly Detection in Beehives using Deep Recurrent Autoencoders P Davidson, M Steininger, F Lautenschlager, K Kobs, A Krause, A Hotho arXiv preprint arXiv:2003.04576, 2020 | 10 | 2020 |
| MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images M Steininger, K Kobs, A Zehe, F Lautenschlager, M Becker, A Hotho ACM Transactions on Spatial Algorithms and Systems (TSAS) 6 (3), 1-24, 2020 | 9 | 2020 |
| Do Different Deep Metric Learning Losses Lead to Similar Learned Features? K Kobs, M Steininger, A Dulny, A Hotho Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 4 | 2021 |
| SimLoss: Class Similarities in Cross Entropy K Kobs, M Steininger, A Zehe, F Lautenschlager, A Hotho International Symposium on Methodologies for Intelligent Systems, 431-439, 2020 | 3 | 2020 |
| Evaluating the multi-task learning approach for land use regression modelling of air pollution A Dulny, M Steininger, F Lautenschlager, A Krause, A Hotho Journal of Physics: Conference Series 1834 (1), 012004, 2021 | 2 | 2021 |
| Semi-Supervised Learning for Grain Size Distribution Interpolation K Kobs, C Schäfer, M Steininger, A Krause, R Baumhauer, H Paeth, ... International Conference on Pattern Recognition, 34-44, 2021 | 2 | 2021 |
| Deep Learning for Climate Model Output Statistics M Steininger, D Abel, K Ziegler, A Krause, H Paeth, A Hotho arXiv preprint arXiv:2012.10394, 2020 | 2 | 2020 |
| Anomaly detection in beehives: An algorithm comparison P Davidson, M Steininger, F Lautenschlager, A Krause, A Hotho Sensor Networks: 9th International Conference, SENSORNETS 2020, Valletta …, 2022 | 1 | 2022 |
| Semi-unsupervised Learning: An In-depth Parameter Analysis P Davidson, F Buckermann, M Steininger, A Krause, A Hotho German Conference on Artificial Intelligence (Künstliche Intelligenz), 51-66, 2021 | 1 | 2021 |
| Detecting Presence Of Speech In Acoustic Data Obtained From Beehives. P Janetzky, P Davidson, M Steininger, A Krause, A Hotho DCASE, 26-30, 2021 | 1 | 2021 |
| InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images K Kobs, M Steininger, A Hotho Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | | 2023 |
| ConvMOS: climate model output statistics with deep learning M Steininger, D Abel, K Ziegler, A Krause, H Paeth, A Hotho Data Mining and Knowledge Discovery, 1-31, 2022 | | 2022 |
| Semi-unsupervised Learning for Time Series Classification P Davidson, M Steininger, A Huhn, A Krause, A Hotho arXiv preprint arXiv:2207.03119, 2022 | | 2022 |
| EveryAware Gears: A Tool to visualize and analyze all types of Citizen Science Data F Lautenschlager, M Becker, M Steininger, A Hotho VGI Geovisual Analytics Workshop, colocated with BDVA 2018, 2018 | | 2018 |
| Appendix for “InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images” K Kobs, M Steininger, A Hotho | | |
Andreas HothoUniversity of WürzburgBestätigte E-Mail-Adresse bei informatik.uni-wuerzburg.de
