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Conference and Workshop Papers
- 2023
[c7]Sophie Henning
, William Beluch, Alexander Fraser, Annemarie Friedrich:
A Survey of Methods for Addressing Class Imbalance in Deep-Learning Based Natural Language Processing. EACL 2023: 523-540- [c6]Dan Zhang, Kaspar Sakmann, William Beluch, Robin Hutmacher, Yumeng Li:
Anomaly-Aware Semantic Segmentation via Style-Aligned OoD Augmentation. ICCV (Workshops) 2023: 4067-4075 - 2021
- [c5]Elias Eulig, Piyapat Saranrittichai, Chaithanya Kumar Mummadi, Kilian Rambach, William Beluch, Xiahan Shi, Volker Fischer:
DiagViB-6: A Diagnostic Benchmark Suite for Vision Models in the Presence of Shortcut and Generalization Opportunities. ICCV 2021: 10635-10644 - [c4]Kanil Patel, William H. Beluch, Bin Yang, Michael Pfeiffer, Dan Zhang:
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning. ICLR 2021 - 2020
- [c3]Kanil Patel, William Beluch, Dan Zhang, Michael Pfeiffer, Bin Yang:
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration. ICPR 2020: 8029-8036 - 2019
- [c2]Jan M. Köhler, Maximilian Autenrieth, William H. Beluch:
Uncertainty Based Detection and Relabeling of Noisy Image Labels. CVPR Workshops 2019: 33-37 - 2018
- [c1]William H. Beluch, Tim Genewein, Andreas Nürnberger, Jan M. Köhler:
The Power of Ensembles for Active Learning in Image Classification. CVPR 2018: 9368-9377
Informal and Other Publications
- 2024
- [i9]Yumeng Li, William Beluch, Margret Keuper, Dan Zhang, Anna Khoreva:
VSTAR: Generative Temporal Nursing for Longer Dynamic Video Synthesis. CoRR abs/2403.13501 (2024) - 2023
- [i8]Dan Zhang, Kaspar Sakmann, William Beluch, Robin Hutmacher, Yumeng Li:
Anomaly-Aware Semantic Segmentation via Style-Aligned OoD Augmentation. CoRR abs/2308.09965 (2023) - 2022
- [i7]Sophie Henning, William H. Beluch, Alexander Fraser, Annemarie Friedrich:
A Survey of Methods for Addressing Class Imbalance in Deep-Learning Based Natural Language Processing. CoRR abs/2210.04675 (2022) - 2021
- [i6]Kanil Patel, William Beluch, Kilian Rambach, Adriana-Eliza Cozma, Michael Pfeiffer, Bin Yang:
Investigation of Uncertainty of Deep Learning-based Object Classification on Radar Spectra. CoRR abs/2106.05870 (2021) - [i5]Elias Eulig, Piyapat Saranrittichai, Chaithanya Kumar Mummadi, Kilian Rambach, William Beluch, Xiahan Shi, Volker Fischer:
DiagViB-6: A Diagnostic Benchmark Suite for Vision Models in the Presence of Shortcut and Generalization Opportunities. CoRR abs/2108.05779 (2021) - [i4]Kanil Patel, William Beluch, Kilian Rambach, Michael Pfeiffer, Bin Yang:
Improving Uncertainty of Deep Learning-based Object Classification on Radar Spectra using Label Smoothing. CoRR abs/2109.12851 (2021) - 2020
- [i3]Kanil Patel, William Beluch, Bin Yang, Michael Pfeiffer, Dan Zhang:
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning. CoRR abs/2006.13092 (2020) - 2019
- [i2]Jan M. Köhler, Maximilian Autenrieth, William H. Beluch:
Uncertainty Based Detection and Relabeling of Noisy Image Labels. CoRR abs/1906.11876 (2019) - [i1]Kanil Patel, William Beluch, Dan Zhang, Michael Pfeiffer, Bin Yang:
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration. CoRR abs/1912.07458 (2019)
Coauthor Index
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