SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data

Alicia Curth, ChangHee Lee, Mihaela van der Schaar. SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data. 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 26740-26753, 2021. [doi]

@inproceedings{CurthLS21,
  title = {SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data},
  author = {Alicia Curth and ChangHee Lee and Mihaela van der Schaar},
  year = {2021},
  url = {https://proceedings.neurips.cc/paper/2021/hash/e0eacd983971634327ae1819ea8b6214-Abstract.html},
  researchr = {https://researchr.org/publication/CurthLS21},
  cites = {0},
  citedby = {0},
  pages = {26740-26753},
  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},
}