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A Sparsity Principle for Partially Observable Causal Representation Learning

2024

Conference Paper

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Author(s): Xu, D. and Yao, D. and Lachapelle, S. and Taslakian, P. and von Kügelgen, J. and Locatello, F. and Magliacane, S.
Book Title: Proceedings of the 41st International Conference on Machine Learning (ICML)
Volume: 235
Pages: 55389--55433
Year: 2024
Month: July

Series: Proceedings of Machine Learning Research
Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix
Publisher: PMLR

Department(s): Empirical Inference
Bibtex Type: Conference Paper (conference)

Event Place: Vienna, Austria

State: Published
URL: https://proceedings.mlr.press/v235/xu24ac.html

BibTex

@conference{Xuetal24,
  title = {A Sparsity Principle for Partially Observable Causal Representation Learning},
  author = {Xu, D. and Yao, D. and Lachapelle, S. and Taslakian, P. and von K{\"u}gelgen, J. and Locatello, F. and Magliacane, S.},
  booktitle = {Proceedings of the 41st International Conference on Machine Learning (ICML)},
  volume = {235},
  pages = {55389--55433},
  series = {Proceedings of Machine Learning Research},
  editors = {Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix},
  publisher = {PMLR},
  month = jul,
  year = {2024},
  doi = {},
  url = {https://proceedings.mlr.press/v235/xu24ac.html},
  month_numeric = {7}
}