Identifiable Generative models for Missing Not at Random Data Imputation

Chao Ma 0019, Cheng Zhang 0005. Identifiable Generative models for Missing Not at Random Data Imputation. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 27645-27658, 2021. [doi]

@inproceedings{MaZ21-13,
  title = {Identifiable Generative models for Missing Not at Random Data Imputation},
  author = {Chao Ma 0019 and Cheng Zhang 0005},
  year = {2021},
  url = {https://proceedings.neurips.cc/paper/2021/hash/e8a642ed6a9ad20fb159472950db3d65-Abstract.html},
  researchr = {https://researchr.org/publication/MaZ21-13},
  cites = {0},
  citedby = {0},
  pages = {27645-27658},
  booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
  editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}