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"

50 / 52 papers shown

Title
Synergizing Deconfounding and Temporal Generalization For Time-series Counterfactual Outcome Estimation Yiling Liu Juncheng Dong Chen Fu Wei Shi Ziyang Jiang Zhigang Hua David Carlson CML 211 0 0 20 Nov 2025
Federated Instrumental Variable Analysis via Federated Generalized Method of Moments Geetika Somya Tyagi Bapi Chatterjee FedML 165 0 0 27 May 2025
A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation Xinran Song Tianyu Chen Mingyuan Zhou DiffM CML 242 0 0 16 May 2025
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 225 1 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 227 0 0 07 Feb 2025
DeCaf: A Causal Decoupling Framework for OOD Generalization on Node ClassificationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Xiaoxue Han Huzefa Rangwala Yue Ning BDL OOD CML 181 1 0 27 Oct 2024
Towards Representation Learning for Weighting Problems in Design-Based Causal InferenceConference on Uncertainty in Artificial Intelligence (UAI), 2024 Oscar Clivio Avi Feller Chris Holmes CML OOD 215 3 0 24 Sep 2024
Causal Effect Estimation using identifiable Variational AutoEncoder with Latent Confounders and Post-Treatment Variables Yang Xie Ziqi Xu Debo Cheng Jiuyong Li Lin Liu Yinghao Zhang Zaiwen Feng CML BDL 130 1 0 13 Aug 2024
PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect Lokesh Nagalapatti Pranava Singhal Avishek Ghosh Sunita Sarawagi CML OOD 248 1 0 06 Jun 2024
Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient Natavsa Tagasovska Vladimir Gligorijević Kyunghyun Cho Andreas Loukas DiffM 221 6 0 28 May 2024
Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation Minqin Zhu Anpeng Wu Haoxuan Li Ruoxuan Xiong Bo Li ... Xuan Qin Peng Zhen Jiecheng Guo Leilei Gan Kun Kuang CML 163 12 0 21 Mar 2024
Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel SmoothingAAAI Conference on Artificial Intelligence (AAAI), 2024 Lokesh Nagalapatti Akshay Iyer Abir De Sunita Sarawagi CML 191 11 0 27 Jan 2024
Neural Causal Abstractions K. Xia Elias Bareinboim CML NAI 269 13 0 05 Jan 2024
Adversarial Distribution Balancing for Counterfactual Reasoning Stefan Schrod Fabian H. Sinz Michael Altenbuchinger OOD CML 211 1 0 28 Nov 2023
Causal inference with Machine Learning-Based Covariate Representation Yuhang Wu Jinghai He Zeyu Zheng CML 136 0 0 03 Nov 2023
Optimal Transport for Treatment Effect EstimationNeural Information Processing Systems (NeurIPS), 2023 Hao Wang Zhichao Chen Jiajun Fan Haoxuan Li Tianqiao Liu Weiming Liu Quanyu Dai Yichao Wang Zhenhua Dong Ruiming Tang OT CML 165 49 0 27 Oct 2023
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML OOD 402 2 0 16 Oct 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 315 16 0 01 Oct 2023
Variational Counterfactual Prediction under Runtime Domain CorruptionIEEE Transactions on Knowledge and Data Engineering (TKDE), 2023 Hechuan Wen Tong Chen L. K. Chai S. Sadiq Junbin Gao Hongzhi Yin OOD 214 2 0 23 Jun 2023
Calibrated and Conformal Propensity Scores for Causal Effect EstimationConference on Uncertainty in Artificial Intelligence (UAI), 2023 Shachi Deshpande Volodymyr Kuleshov CML 290 1 0 01 Jun 2023
Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities Connor Jerzak Fredrik D. Johansson Adel Daoud CML 162 15 0 30 Jan 2023
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 262 17 0 07 Nov 2022
Nonlinear Causal Discovery via Kernel Anchor Regression Wenqi Shi Wenkai Xu CML BDL 146 0 0 30 Oct 2022
Causal Inference for De-biasing Motion Estimation from Robotic Observational DataIEEE International Conference on Robotics and Automation (ICRA), 2022 Junhong Xu Kai-Li Yin Jason M. Gregory Lantao Liu CML 153 4 0 17 Oct 2022
Causal Inference for Chatting Handoff Shan Zhong Jinghui Qin Zhongzhan Huang Daifeng Li 121 0 0 06 Oct 2022
Neural Causal Models for Counterfactual Identification and Estimation K. Xia Yushu Pan Elias Bareinboim CML 230 54 0 30 Sep 2022
Image-based Treatment Effect HeterogeneityCLEaR (CLEaR), 2022 Connor Jerzak Fredrik D. Johansson Adel Daoud 416 28 0 13 Jun 2022
Estimating Causal Effects Under Image Confounding Bias with an Application to Poverty in Africa Connor Jerzak Fredrik D. Johansson Adel Daoud CML 305 6 0 13 Jun 2022
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured ProxiesNeural Information Processing Systems (NeurIPS), 2022 Shachi Deshpande Kaiwen Wang Dhruv Sreenivas Zheng Li Volodymyr Kuleshov CML SyDa 253 13 0 18 Mar 2022
Outcome Assumptions and Duality Theory for Balancing WeightsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 David Bruns-Smith Avi Feller 150 6 0 17 Mar 2022
Neural Score Matching for High-Dimensional Causal InferenceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Oscar Clivio Fabian Falck B. Lehmann George Deligiannidis Chris Holmes CML 167 9 0 01 Mar 2022
Estimating causal effects with optimization-based methods: A review and empirical comparisonEuropean Journal of Operational Research (EJOR), 2022 Martin Cousineau V. Verter Susan Murphy J. Pineau CML 137 11 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 311 33 0 02 Feb 2022
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal EffectsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 Yao Zhang Jeroen Berrevoets M. Schaar CML 271 6 0 06 Aug 2021
The Causal-Neural Connection: Expressiveness, Learnability, and Inference K. Xia Kai-Zhan Lee Yoshua Bengio Elias Bareinboim CML 271 128 0 02 Jul 2021
Finding Valid Adjustments under Non-ignorability with Minimal DAG KnowledgeInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 Abhin Shah Karthikeyan Shanmugam Kartik Ahuja CML 148 13 0 22 Jun 2021
Causal Effect Inference for Structured TreatmentsNeural Information Processing Systems (NeurIPS), 2021 Jean Kaddour Yuchen Zhu Qi Liu Matt J. Kusner Ricardo M. A. Silva CML 444 53 0 03 Jun 2021
Matched sample selection with GANs for mitigating attribute confounding Chandan Singh Guha Balakrishnan Pietro Perona GAN 141 7 0 24 Mar 2021
Treatment Effect Estimation using Invariant Risk MinimizationIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021 Abhin Shah Kartik Ahuja Karthikeyan Shanmugam Dennis L. Wei Kush R. Varshney Amit Dhurandhar CML OOD 95 3 0 13 Mar 2021
Treatment Targeting by AUUC Maximization with Generalization Guarantees Artem Betlei Eustache Diemert Massih-Reza Amini CML 117 5 0 17 Dec 2020
Adversarial Counterfactual Learning and Evaluation for Recommender System Da Xu Chuanwei Ruan Evren Körpeoglu Sushant Kumar Kannan Achan OffRL CML 139 34 0 08 Nov 2020
High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation Kristjan Greenewald Dmitriy A. Katz-Rogozhnikov Karthikeyan Shanmugam CML 190 9 0 03 Nov 2020
Counterfactual Representation Learning with Balancing WeightsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Serge Assaad Shuxi Zeng Chenyang Tao Shounak Datta Nikhil Mehta Ricardo Henao Fan Li Lawrence Carin CML OOD 337 77 0 23 Oct 2020
Sufficient Dimension Reduction for Average Causal Effect EstimationData mining and knowledge discovery (DMKD), 2020 Debo Cheng Jiuyong Li Lin Liu Jixue Liu CML 147 15 0 14 Sep 2020
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal EffectsJournal of machine learning research (JMLR), 2020 Fredrik D. Johansson Uri Shalit Nathan Kallus David Sontag CML OOD 328 119 0 21 Jan 2020
The Counterfactual $χ$ -GANJournal of Biomedical Informatics (JBI), 2020 A. Averitt Natnicha Vanitchanant Rajesh Ranganath A. Perotte CML BDL 96 8 0 09 Jan 2020
Deep Generalized Method of Moments for Instrumental Variable AnalysisNeural Information Processing Systems (NeurIPS), 2019 Andrew Bennett Nathan Kallus Tobias Schnabel 179 137 0 29 May 2019
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational DataData mining and knowledge discovery (DMKD), 2019 Xin Du Lei Sun W. Duivesteijn Alexander G. Nikolaev Mykola Pechenizkiy OOD CML 153 47 0 30 Apr 2019
Synthetic learner: model-free inference on treatments over time Davide Viviano Jelena Bradic CML 276 21 0 02 Apr 2019
Stochastic Doubly Robust Gradient Kanghoon Lee Jihye Choi Moonsu Cha Jung Kwon Lee Tae-Yoon Kim 72 0 0 21 Dec 2018