Rui Li, Stephanie Hu, Mingyu Lu, Yuria Utsumi, Prithwish Chakraborty, Daby M. Sow, Piyush Madan, Jun Li, Mohamed Ghalwash, Zach Shahn, Li-Wei H. Lehman. G-Net: a Recurrent Network Approach to G-Computation for Counterfactual Prediction Under a Dynamic Treatment Regime. In Subhrajit Roy, Stephen Pfohl, Emma Rocheteau, Girmaw Abebe Tadesse, Luis Oala, Fabian Falck, Yuyin Zhou, Liyue Shen, Ghada Zamzmi, Purity Mugambi, Ayah Zirikly, Matthew B. A. McDermott, Emily Alsentzer, editors, Machine Learning for Health, ML4H@NeurIPS 2021, 04 December 2021, Virtual Event. Volume 158 of Proceedings of Machine Learning Research, pages 282-299, PMLR, 2021. [doi]
@inproceedings{LiHLUCSMLGSL21,
title = {G-Net: a Recurrent Network Approach to G-Computation for Counterfactual Prediction Under a Dynamic Treatment Regime},
author = {Rui Li and Stephanie Hu and Mingyu Lu and Yuria Utsumi and Prithwish Chakraborty and Daby M. Sow and Piyush Madan and Jun Li and Mohamed Ghalwash and Zach Shahn and Li-Wei H. Lehman},
year = {2021},
url = {https://proceedings.mlr.press/v158/li21a.html},
researchr = {https://researchr.org/publication/LiHLUCSMLGSL21},
cites = {0},
citedby = {0},
pages = {282-299},
booktitle = {Machine Learning for Health, ML4H@NeurIPS 2021, 04 December 2021, Virtual Event},
editor = {Subhrajit Roy and Stephen Pfohl and Emma Rocheteau and Girmaw Abebe Tadesse and Luis Oala and Fabian Falck and Yuyin Zhou and Liyue Shen and Ghada Zamzmi and Purity Mugambi and Ayah Zirikly and Matthew B. A. McDermott and Emily Alsentzer},
volume = {158},
series = {Proceedings of Machine Learning Research},
publisher = {PMLR},
}