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Empirical Inference Conference Paper 2022

Towards Principled Disentanglement for Domain Generalization

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Empirical Inference
Bernhard Schölkopf
  • Director
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Empirical Inference
Weiyang Liu
  • Postdoctoral Researcher

Author(s): Zhang, H. and Zhang, Y.-F. and Liu, W. and Weller, A. and Schölkopf, B. and Xing, E.
Book Title: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Pages: 8024--8034
Year: 2022
Month: June
Bibtex Type: Conference Paper (conference)
Event Place: New Orleans, Louisiana
State: Published
URL: https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_Towards_Principled_Disentanglement_for_Domain_Generalization_CVPR_2022_paper.pdf
Electronic Archiving: grant_archive
Supplement: https://openaccess.thecvf.com/content/CVPR2022/supplemental/Zhang_Towards_Principled_Disentanglement_CVPR_2022_supplemental.pdf
Links:

BibTex 

@conference{Zhangetal22b,
  title = {Towards Principled Disentanglement for Domain Generalization},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages = {8024--8034},
  month = jun,
  year = {2022},
  slug = {zhangetal22b},
  author = {Zhang, H. and Zhang, Y.-F. and Liu, W. and Weller, A. and Sch{\"o}lkopf, B. and Xing, E.},
  url = {https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_Towards_Principled_Disentanglement_for_Domain_Generalization_CVPR_2022_paper.pdf},
  month_numeric = {6}
}