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Michael Kirchhof
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Development and implementation of statistical methods for quality optimization in the large‐format lithium‐ion cells production
O Meyer, C Weihs, S Mähr, HY Tran, M Kirchhof, S Schnackenberg, ...
Energy Technology 8 (2), 1900244, 2020
172020
A non-isotropic probabilistic take on proxy-based deep metric learning
M Kirchhof, K Roth, Z Akata, E Kasneci
European Conference on Computer Vision (ECCV 2022), 435-454, 2022
162022
Probabilistic contrastive learning recovers the correct aleatoric uncertainty of ambiguous inputs
M Kirchhof, E Kasneci, SJ Oh
International Conference on Machine Learning (ICML 2023), 2023
152023
Root Cause Analysis in Lithium-ion Battery Production with FMEA-based Large-scale Bayesian Network
M Kirchhof, K Haas, T Kornas, S Thiede, M Hirz, C Herrmann
arXiv preprint arXiv:2006.03610, 2020
132020
When are post-hoc conceptual explanations identifiable?
T Leemann, M Kirchhof, Y Rong, E Kasneci, G Kasneci
Uncertainty in Artificial Intelligence (UAI 2023), 1207-1218, 2023
12*2023
Chances of interpretable transfer learning for human activity recognition in warehousing
M Kirchhof, L Schmid, C Reining, M Hompel, M Pauly
Computational Logistics: 12th International Conference, ICCL 2021, Enschede …, 2021
82021
URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates
M Kirchhof, B Mucsányi, SJ Oh, E Kasneci
NeurIPS 2023 Datasets and Benchmarks, 2023
72023
pRSL: Interpretable Multi-label Stacking by Learning Probabilistic Rules
M Kirchhof, L Schmid, C Reining, M ten Hompel, M Pauly
Uncertainty in Artificial Intelligence (UAI 2021), 2021
62021
Pretrained Visual Uncertainties
M Kirchhof, M Collier, SJ Oh, E Kasneci
arXiv preprint arXiv:2402.16569, 2024
42024
Benchmarking uncertainty disentanglement: Specialized uncertainties for specialized tasks
B Mucsányi, M Kirchhof, SJ Oh
arXiv preprint arXiv:2402.19460, 2024
32024
Trustworthy machine learning
B Mucsányi, M Kirchhof, E Nguyen, A Rubinstein, SJ Oh
arXiv preprint arXiv:2310.08215, 2023
22023
Cutting Optimal Pieces from Production Items
M Kirchhof, O Meyer, C Weihs
12019
Uncertainties of Latent Representations in Computer Vision
M Kirchhof
PhD thesis, Universität Tübingen, 2024
2024
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