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Empirical Inference Conference Paper 2021

Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings

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Empirical Inference
Zhijing Jin
  • Postdoctoral Researcher

Author(s): Guo, Q. and Jin, Z. and Wang, Z. and Qiu, X. and Zhang, W. and Zhu, J. and Zhang, Z. and Wipf, D.
Book Title: Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS)
Volume: 130
Pages: 1828--1836
Year: 2021
Month: April
Series: Proceedings of Machine Learning Research
Editors: Arindam Banerjee and Kenji Fukumizu
Publisher: PMLR
Bibtex Type: Conference Paper (conference)
Event Name: AISTATS 2021
Event Place: Virtual Conference
State: Published
URL: http://proceedings.mlr.press/v130/guo21b.html
Electronic Archiving: grant_archive
Attachments:

BibTex 

@conference{Guoetal21,
  title = {Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings},
  booktitle = {Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS)},
  volume = {130},
  pages = {1828--1836},
  series = {Proceedings of Machine Learning Research},
  editors = {Arindam Banerjee and Kenji Fukumizu},
  publisher = {PMLR},
  month = apr,
  year = {2021},
  slug = {guoetal21},
  author = {Guo, Q. and Jin, Z. and Wang, Z. and Qiu, X. and Zhang, W. and Zhu, J. and Zhang, Z. and Wipf, D.},
  url = {http://proceedings.mlr.press/v130/guo21b.html},
  month_numeric = {4}
}