DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training

15 February 2018

Papers citing "DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training"

18 / 18 papers shown

Title
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective Hechuan Wen Tong Chen Mingming Gong Li Kheng Chai S. Sadiq Hongzhi Yin CML 60 0 0 08 May 2025
Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE Lokesh Nagalapatti Pranava Singhal Avishek Ghosh Sunita Sarawagi CML 81 0 0 07 Feb 2025
Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient Natavsa Tagasovska Vladimir Gligorijević Kyunghyun Cho Andreas Loukas DiffM 52 4 0 28 May 2024
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML OOD 71 2 0 16 Oct 2023
Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities Connor Jerzak Fredrik D. Johansson Adel Daoud CML 41 11 0 30 Jan 2023
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 36 11 0 07 Nov 2022
Causal Inference for De-biasing Motion Estimation from Robotic Observational Data Junhong Xu Kai-Li Yin Jason M. Gregory Lantao Liu CML 23 3 0 17 Oct 2022
Neural Causal Models for Counterfactual Identification and Estimation K. Xia Yushu Pan Elias Bareinboim CML 45 32 0 30 Sep 2022
Image-based Treatment Effect Heterogeneity Connor Jerzak Fredrik D. Johansson Adel Daoud 32 20 0 13 Jun 2022
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies Shachi Deshpande Kaiwen Wang Dhruv Sreenivas Zheng Li Volodymyr Kuleshov CML SyDa 16 11 0 18 Mar 2022
Estimating causal effects with optimization-based methods: A review and empirical comparison Martin Cousineau V. Verter S. Murphy J. Pineau CML 24 9 0 28 Feb 2022
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation Yi-Fan Zhang Hanlin Zhang Zachary Chase Lipton Li Erran Li Eric P. Xing OODD 24 29 0 02 Feb 2022
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects Yao Zhang Jeroen Berrevoets M. Schaar CML 36 5 0 06 Aug 2021
Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge Abhin Shah Karthikeyan Shanmugam Kartik Ahuja CML 36 12 0 22 Jun 2021
High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation Kristjan Greenewald Dmitriy A. Katz-Rogozhnikov Karthikeyan Shanmugam CML 39 9 0 03 Nov 2020
Synthetic learner: model-free inference on treatments over time Davide Viviano Jelena Bradic CML 22 19 0 02 Apr 2019
Adversarial Balancing for Causal Inference Michal Ozery-Flato Pierre Thodoroff Matan Ninio Michal Rosen-Zvi T. El-Hay CML GAN 16 25 0 17 Oct 2018
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 232 719 0 12 May 2016