Deep Counterfactual Networks with Propensity-Dropout

19 June 2017

Papers citing "Deep Counterfactual Networks with Propensity-Dropout"

21 / 21 papers shown

Title
Consistent Causal Inference of Group Effects in Non-Targeted Trials with Finitely Many Effect Levels Georgios Mavroudeas M. Magdon-Ismail Kristin P. Bennett Jason Kuruzovich 34 0 0 22 Apr 2025
Enhancing predictive imaging biomarker discovery through treatment effect analysis Shuhan Xiao Lukas Klein Jens Petersen Philipp Vollmuth Paul F. Jaeger Klaus H. Maier-Hein 34 0 0 04 Jun 2024
VLUCI: Variational Learning of Unobserved Confounders for Counterfactual Inference Yonghe Zhao Q. Huang Siwei Wu Yun Peng H. Sun BDL CML 21 0 0 02 Aug 2023
Deep Causal Learning for Robotic Intelligence Yongqian Li CML 48 5 0 23 Dec 2022
TCFimt: Temporal Counterfactual Forecasting from Individual Multiple Treatment Perspective Pengfei Xi Guifeng Wang Zhipeng Hu Yu Xiong Ming‐Fu Gong ... Runze Wu Yu-qiong Ding Tangjie Lv Changjie Fan Xiangnan Feng CML AI4TS AI4CE 20 0 0 17 Dec 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 41 11 0 07 Nov 2022
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation Ioana Bica M. Schaar OOD CML 40 20 0 08 Oct 2022
Is More Data All You Need? A Causal Exploration Athanasios Vlontzos Hadrien Reynaud Bernhard Kainz CML 29 2 0 06 Jun 2022
Toward Data-Driven Digital Therapeutics Analytics: Literature Review and Research Directions Uichin Lee Gyuwon Jung Eun-Yeol Ma Jinsan Kim Heepyung Kim Jumabek Alikhanov Youngtae Noh Heeyoung Kim 21 20 0 04 May 2022
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation Yi-Fan Zhang Hanlin Zhang Zachary Chase Lipton Li Erran Li Eric P. Xing OODD 33 30 0 02 Feb 2022
Estimating Categorical Counterfactuals via Deep Twin Networks Athanasios Vlontzos Bernhard Kainz Ciarán M. Gilligan-Lee OOD CML BDL 28 16 0 04 Sep 2021
The Bias-Variance Tradeoff of Doubly Robust Estimator with Targeted $L_1$ regularized Neural Networks Predictions M. Rostami O. Saarela M. Escobar 45 1 0 02 Aug 2021
Time Series Forecasting With Deep Learning: A Survey Bryan Lim S. Zohren AI4TS AI4CE 59 1,192 0 28 Apr 2020
G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes Rui Li Zach Shahn Jun Li Mingyu Lu Prithwish Chakraborty Daby M. Sow Mohamed F. Ghalwash Li-wei H. Lehman CML AI4CE PINN BDL 19 12 0 23 Mar 2020
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks Ioana Bica James Jordon M. Schaar CML 32 105 0 27 Feb 2020
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves Patrick Schwab Lorenz Linhardt Stefan Bauer J. M. Buhmann W. Karlen CML OOD 34 132 0 03 Feb 2019
Deconfounding Reinforcement Learning in Observational Settings Chaochao Lu Bernhard Schölkopf José Miguel Hernández-Lobato CML OOD 39 73 0 26 Dec 2018
Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks Patrick Schwab Lorenz Linhardt W. Karlen CML BDL 21 111 0 01 Oct 2018
A Bayesian Nonparametric Approach for Estimating Individualized Treatment-Response Curves Yanbo Xu Yanxun Xu Suchi Saria CML 64 40 0 18 Aug 2016
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 232 722 0 12 May 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 289 9,167 0 06 Jun 2015