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Nadine Behrmann
Nadine Behrmann
Applied Scientist at Amazon
Подтвержден адрес электронной почты в домене amazon.de
Название
Процитировано
Процитировано
Год
Unified fully and timestamp supervised temporal action segmentation via sequence to sequence translation
N Behrmann, SA Golestaneh, Z Kolter, J Gall, M Noroozi
European conference on computer vision, 52-68, 2022
942022
Ranking info noise contrastive estimation: Boosting contrastive learning via ranked positives
DT Hoffmann, N Behrmann, J Gall, T Brox, M Noroozi
Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 897-905, 2022
472022
Long short view feature decomposition via contrastive video representation learning
N Behrmann, M Fayyaz, J Gall, M Noroozi
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
442021
Unsupervised video representation learning by bidirectional feature prediction
N Behrmann, J Gall, M Noroozi
Proceedings of the IEEE/CVF winter conference on applications of computer …, 2021
362021
Eureka-moments in transformers: multi-step tasks reveal softmax induced optimization problems
DT Hoffmann, S Schrodi, J Bratulić, N Behrmann, V Fischer, T Brox
arXiv preprint arXiv:2310.12956, 2023
72023
Segmentation of a sequence of video images with a transformer network
N Behrmann, M Noroozi, SA Golestaneh
US Patent App. 18/308,452, 2023
12023
Unsupervised training of a video feature extractor
M Noroozi, N Behrmann
US Patent 11,921,817, 2024
2024
Self-Supervised Video Representation Learning and Downstream Applications
N Behrmann
Dissertation, Bonn, Rheinische Friedrich-Wilhelms-Universität, 2023, 2023
2023
Method for coding a sequence of video images
M Noroozi, M Fayyaz, N Behrmann
US Patent App. 17/859,611, 2023
2023
Contrastive representation learning for measurement data
D Hoffmann, M Noroozi, N Behrmann
US Patent App. 17/812,211, 2023
2023
Unified Fully and Timestamp Supervised Temporal Action Segmentation via Sequence to Sequence Translation Supplementary Material
N Behrmann, SA Golestaneh, Z Kolter, J Gall, M Noroozi
Meta-Learning Runge-Kutta
N Behrmann, P Schramowski, K Kersting
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