Jan Mathias Köhler
Jan Mathias Köhler
Enable AI / Bosch Center for Artificial Intelligence
Verified email at - Homepage
Cited by
Cited by
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
Weakly-supervised localization of diabetic retinopathy lesions in retinal fundus images
WM Gondal, JM Köhler, R Grzeszick, GA Fink, M Hirsch
2017 IEEE international conference on image processing (ICIP), 2069-2073, 2017
Interpretable and fine-grained visual explanations for convolutional neural networks
J Wagner, JM Kohler, T Gindele, L Hetzel, JT Wiedemer, S Behnke
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
Variational network quantization
J Achterhold, JM Koehler, A Schmeink, T Genewein
International conference on learning representations, 2018
Uncertainty Based Detection and Relabeling of Noisy Image Labels.
JM Köhler, M Autenrieth, WH Beluch
CVPR workshops, 33-37, 2019
Bounded flexibility in days‐on and days‐off scheduling
JO Brunner, JF Bard, JM Köhler
Naval Research Logistics (NRL) 60 (8), 678-701, 2013
The streaming rollout of deep networks-towards fully model-parallel execution
V Fischer, J Köhler, T Pfeil
Advances in Neural Information Processing Systems 31, 2018
A neutral triple-helical trinuclear oxo-centered mixed-valent iron complex: Mössbauer spectroscopic and magnetic susceptibility studies
V Coropceanu, V Schünemann, C Ober, M Gerdan, AX Trautwein, ...
Inorganica Chimica Acta 300, 875-881, 2000
Omega-3 index and obstructive sleep apnea: a cross-sectional study
J Tittus, MT Huber, K Storck, A Köhler, JM Köhler, T von Arnim, ...
Journal of Clinical Sleep Medicine 13 (10), 1131-1136, 2017
Method, device and computer program for creating a deep neural network
J Achterhold, JM Koehler, T Genewein
US Patent 11,531,888, 2022
Mind the Gap Between Synthetic and Real: Utilizing Transfer Learning to Probe the Boundaries of Stable Diffusion Generated Data
L Hennicke, CM Adriano, H Giese, JM Koehler, L Schott
arXiv preprint arXiv:2405.03243, 2024
Challenging Common Assumptions in Multi-task Learning
C Elich, L Kirchdorfer, JM Köhler, L Schott
arXiv preprint arXiv:2311.04698, 2023
Processing of learning data sets including noisy labels for classifiers
WH Beluch, JM Koehler, M Autenrieth
US Patent App. 17/233,410, 2021
Method and device for ascertaining an explanation map
J Wagner, T Gindele, JM Koehler, JT Wiedemer, L Hetzel
US Patent 11,783,190, 2023
Method and device for ascertaining an explanation map
J Wagner, T Gindele, JM Koehler, JT Wiedemer, L Hetzel
US Patent 11,645,828, 2023
Discretization of numerical values with adaptive accuracy
JM Koehler, RM Koehler
US Patent 11,488,006, 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
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
Method and device for ascertaining a gradient of a data-based function model
M Hanselmann, JM Koehler, H Markert
US Patent 10,402,509, 2019
Flexible days off scheduling: A general approach
J Brunner, JM Köhler
International Annual Scientific Conference of the German Operations Research …, 2011
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