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@inproceedings{haeusser_iccv_17,
author = {P. Haeusser and T. Frerix and A. Mordvintsev and D. Cremers},
title = {Associative Domain Adaptation},
booktitle = {IEEE International Conference on Computer Vision (ICCV)},
year = {2017},
keywords = {semi-supervised, deep learning, neural networks, association, domain adaptation, associative_learning},
titleurl = {haeusser_iccv_17.pdf},
}
@inproceedings{Frerix-et-al-18,
author = {T. Frerix and T. Möllenhoff and M. Moeller and D. Cremers},
title = {Proximal Backpropagation},
booktitle = {International Conference on Learning Representations (ICLR)},
primaryclass = {cs.LG},
year = {2018},
}
@inproceedings{Frerix2020,
author = {T Frerix and M Nießner and D Cremers},
title = {Homogeneous Linear Inequality Constraints for Neural Network Activations},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
year = {2020},
}
@inproceedings{Frerix2021,
title = {Variational Data Assimilation with a Learned Inverse Observation Operator},
author = {T Frerix and D Kochkov and J Smith and D Cremers and M Brenner and S Hoyer},
booktitle = {Proceedings of the 38th International Conference on Machine Learning (ICML)},
year = {2021},
}
@inproceedings{Frerix2019-givens,
title = {{Approximating Orthogonal Matrices with Effective Givens Factorization}},
author = {T. Frerix and J. Bruna},
booktitle = {Proceedings of the 36th International Conference on Machine Learning (ICML)},
year = {2019},
}