Deep Counterfactual Networks with Propensity-Dropout

19 June 2017

Papers citing "Deep Counterfactual Networks with Propensity-Dropout"

43 / 43 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 59 0 0 22 Apr 2025
Are causal effect estimations enough for optimal recommendations under multitreatment scenarios? Sherly Alfonso-Sánchez Kristina P. Sendova Cristián Bravo CML 41 0 0 07 Oct 2024
Ads Supply Personalization via Doubly Robust Learning Wei Shi Chen Fu Qi Xu Sanjian Chen Jizhe Zhang Qinqin Zhu Zhigang Hua Shuang Yang OffRL 66 1 0 29 Sep 2024
MSCT: Addressing Time-Varying Confounding with Marginal Structural Causal Transformer for Counterfactual Post-Crash Traffic Prediction Shuang Li Ziyuan Pu Nan Zhang Duxin Chen Lu Dong Daniel J. Graham Yinhai Wang 112 0 0 19 Jul 2024
Causal Inference with Complex Treatments: A Survey Yingrong Wang Haoxuan Li Minqin Zhu Anpeng Wu Ruoxuan Xiong Leilei Gan Kun Kuang CML 86 1 0 19 Jul 2024
Enhancing predictive imaging biomarker discovery through treatment effect analysis Shuhan Xiao Lukas Klein Jens Petersen Philipp Vollmuth Paul F. Jaeger Klaus H. Maier-Hein 50 0 0 04 Jun 2024
A Review and Roadmap of Deep Causal Model from Different Causal Structures and Representations Hang Chen Keqing Du Chenguang Li Xinyu Yang 100 2 0 02 Nov 2023
Towards Causal Foundation Model: on Duality between Causal Inference and Attention Jiaqi Zhang Joel Jennings Agrin Hilmkil Nick Pawlowski Cheng Zhang Chao Ma CML 112 14 0 01 Oct 2023
VLUCI: Variational Learning of Unobserved Confounders for Counterfactual Inference Yonghe Zhao Q. Huang Siwei Wu Yun Peng Huashan Sun BDL CML 32 0 0 02 Aug 2023
Assisting Clinical Decisions for Scarcely Available Treatment via Disentangled Latent Representation Bing Xue A. Said Ziqi Xu Hanyang Liu N. Shah Hanqing Yang Philip R. O. Payne Chenyang Lu 126 5 0 06 Jul 2023
DR-VIDAL -- Doubly Robust Variational Information-theoretic Deep Adversarial Learning for Counterfactual Prediction and Treatment Effect Estimation on Real World Data Shantanu Ghosh Zheng Feng Jiang Bian Kevin R. B. Butler M. Prosperi CML OOD BDL 21 0 0 07 Mar 2023
Estimating Causal Effects using a Multi-task Deep Ensemble Ziyang Jiang Zhuoran Hou Yi-Ling Liu Yiman Ren Keyu Li David Carlson CML 76 6 0 26 Jan 2023
Deep Causal Learning for Robotic Intelligence Yongqian Li CML 73 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 49 0 0 17 Dec 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 119 11 0 07 Nov 2022
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation Ioana Bica M. Schaar OOD CML 70 22 0 08 Oct 2022
A Survey of Deep Causal Models and Their Industrial Applications Zongyu Li Xiaoning Guo Siwei Qiang CML AI4CE 76 8 0 19 Sep 2022
Adversarial Counterfactual Environment Model Learning Xiong-Hui Chen Yang Yu Zhenghong Zhu Zhihua Yu Zhen-Yu Chen ... Yinan Wu Hongqiu Wu Rongjun Qin Rui Ding Fangsheng Huang CML OffRL 91 12 0 10 Jun 2022
Is More Data All You Need? A Causal Exploration Athanasios Vlontzos Hadrien Reynaud Bernhard Kainz CML 63 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 26 21 0 04 May 2022
Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation Kan Chen Qishuo Yin Q. Long CML 68 5 0 07 Mar 2022
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation Yi-Fan Zhang Hanlin Zhang Zachary Chase Lipton Li Erran Li Eric P. Xing OODD 115 30 0 02 Feb 2022
Non parametric estimation of causal populations in a counterfactual scenario Céline Beji Florian Yger Jamal Atif CML OOD 32 0 0 08 Dec 2021
Estimating Potential Outcome Distributions with Collaborating Causal Networks Tianhui Zhou William E Carson IV David Carlson CML 208 8 0 04 Oct 2021
Estimating Categorical Counterfactuals via Deep Twin Networks Athanasios Vlontzos Bernhard Kainz Ciarán M. Gilligan-Lee OOD CML BDL 113 17 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 70 1 0 02 Aug 2021
On Inductive Biases for Heterogeneous Treatment Effect Estimation Alicia Curth M. Schaar CML 193 84 0 07 Jun 2021
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge Trent Kyono Ioana Bica Zhaozhi Qian Mihaela van der Schaar OOD CML 25 7 0 11 Feb 2021
Learning Matching Representations for Individualized Organ Transplantation Allocation Can Xu Ahmed Alaa Ioana Bica B. Ershoff M. Cannesson M. Schaar OOD 49 7 0 28 Jan 2021
Balance Regularized Neural Network Models for Causal Effect Estimation Mehrdad Farajtabar Andrew Lee Yuanjian Feng Vishal Gupta Peter Dolan Harish Chandran M. Szummer CML 46 6 0 23 Nov 2020
Representation Learning for Integrating Multi-domain Outcomes to Optimize Individualized Treatments Yuan Chen D. Zeng Tianchen Xu Yuanjia Wang AI4CE 46 3 0 30 Oct 2020
Adapting Neural Networks for Uplift Models Mouloud Belbahri Olivier Gandouet Ghaith Kazma 45 11 0 30 Oct 2020
Rank Position Forecasting in Car Racing Bo Peng Jiayu Li Selahattin Akkas Fugang Wang Takuya Araki Ohno Yoshiyuki J. Qiu BDL 55 6 0 04 Oct 2020
Time Series Forecasting With Deep Learning: A Survey Bryan Lim S. Zohren AI4TS AI4CE 126 1,249 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 44 13 0 23 Mar 2020
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks Ioana Bica James Jordon M. Schaar CML 90 106 0 27 Feb 2020
A Survey on Causal Inference Liuyi Yao Zhixuan Chu Sheng Li Yaliang Li Jing Gao Aidong Zhang CML 117 516 0 05 Feb 2020
FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles Ana Lucic Harrie Oosterhuis H. Haned Maarten de Rijke LRM 90 63 0 27 Nov 2019
Adapting Neural Networks for the Estimation of Treatment Effects Claudia Shi David M. Blei Victor Veitch CML 159 376 0 05 Jun 2019
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves Patrick Schwab Lorenz Linhardt Stefan Bauer J. M. Buhmann W. Karlen CML OOD 101 135 0 03 Feb 2019
Deconfounding Reinforcement Learning in Observational Settings Chaochao Lu Bernhard Schölkopf José Miguel Hernández-Lobato CML OOD 173 75 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 102 111 0 01 Oct 2018
Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms Ahmed Alaa Mihaela van der Schaar CML 70 43 0 24 Dec 2017