| The power of ensembles for active learning in image classification WH Beluch, T Genewein, A Nürnberger, JM Köhler Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 822 | 2018 |
| An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice JPL Castro, MN Yancoskie, M Marchini, S Belohlavy, L Hiramatsu, ... elife 8, e42014, 2019 | 59 | 2019 |
| Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning K Patel, W Beluch, B Yang, M Pfeiffer, D Zhang International Conference on Learning Representations, ICLR 2021, 2020 | 41 | 2020 |
| Uncertainty Based Detection and Relabeling of Noisy Image Labels. JM Köhler, M Autenrieth, WH Beluch CVPR workshops, 33-37, 2019 | 34 | 2019 |
| A survey of methods for addressing class imbalance in deep-learning based natural language processing S Henning, W Beluch, A Fraser, A Friedrich arXiv preprint arXiv:2210.04675, 2022 | 28 | 2022 |
| On-manifold adversarial data augmentation improves uncertainty calibration K Patel, W Beluch, D Zhang, M Pfeiffer, B Yang International Conference on Pattern Recognition, ICPR 2020, 2019 | 28 | 2019 |
| Investigation of uncertainty of deep learning-based object classification on radar spectra K Patel, W Beluch, K Rambach, AE Cozma, M Pfeiffer, B Yang 2021 IEEE Radar Conference (RadarConf21), 1-6, 2021 | 15 | 2021 |
| Diagvib-6: A diagnostic benchmark suite for vision models in the presence of shortcut and generalization opportunities E Eulig, P Saranrittichai, CK Mummadi, K Rambach, W Beluch, X Shi, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 9 | 2021 |
| The power of ensembles for active learning in image classification. In 2018 IEEE WH Beluch, T Genewein, A Nurnberger, JM Kohler CVF Conference on Computer Vision and Pattern Recognition, 9368-9377, 0 | 8 | |
| Adherence to oral tyrosine kinase inhibitor therapy: results of a self-reported patient survey SL Goldberg, MS Aioub, WH Beluch, LS Kaplan, T Singh, J Shah, ... Blood 118 (21), 4432, 2011 | 4 | 2011 |
| VSTAR: Generative Temporal Nursing for Longer Dynamic Video Synthesis Y Li, W Beluch, M Keuper, D Zhang, A Khoreva arXiv preprint arXiv:2403.13501, 2024 | 3 | 2024 |
| Anomaly-aware semantic segmentation via style-aligned ood augmentation D Zhang, K Sakmann, W Beluch, R Hutmacher, Y Li Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 3 | 2023 |
| Independent evolution toward larger body size in the distinctive Faroe Island mice R Wilches, WH Beluch, E McConnell, D Tautz, YF Chan G3 11 (1), jkaa051, 2021 | 3 | 2021 |
| Processing of learning data sets including noisy labels for classifiers WH Beluch, JM Koehler, M Autenrieth US Patent App. 17/233,410, 2021 | 1 | 2021 |
| Prioritizing training examples when training classifiers L Beggel, WH Beluch US Patent App. 18/182,215, 2024 | | 2024 |
| Image generation model based on log-likelihood E Hoogeboom, D Nielsen, M Welling, P Forre, P Jaini, WH Beluch US Patent 11,995,151, 2024 | | 2024 |
| Image analysis model comprising a discrete coupling layer A Lindt, E Hoogeboom, WH Beluch US Patent App. 17/650,779, 2022 | | 2022 |
| Image analysis model comprising an integer coupling layer A Lindt, E Hoogeboom, WH Beluch US Patent App. 17/650,786, 2022 | | 2022 |
| Operation of trainable modules, including monitoring as to whether the range of application of the training is abandoned JM Koehler, M Autenrieth, WH Beluch US Patent App. 17/611,088, 2022 | | 2022 |
| Training trainable modules using learning data, the labels of which are subject to noise JM Koehler, M Autenrieth, WH Beluch US Patent App. 17/420,357, 2022 | | 2022 |
