Causal Effect Estimation: Recent Advances, Challenges, and Opportunities

Causal Effect Estimation: Recent Advances, Challenges, and Opportunities

2 February 2023

Papers citing "Causal Effect Estimation: Recent Advances, Challenges, and Opportunities"

12 / 12 papers shown

Title
Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimization Min Cheng Xinru Liao Quanlian Liu Bin Ma Jian Xu Bo Zheng CML 48 25 0 02 Jun 2022
Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data Zhixuan Chu S. Rathbun Sheng Li CML 31 48 0 05 Jun 2021
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments Lizhen Nie Mao Ye Qiang Liu D. Nicolae CML 52 71 0 14 Mar 2021
Cycle Self-Training for Domain Adaptation Hong Liu Jianmin Wang Mingsheng Long 93 177 0 05 Mar 2021
Learning Decomposed Representation for Counterfactual Inference Anpeng Wu Kun Kuang Junkun Yuan Bo Li Jianrong Tao Qiang Zhu Yueting Zhuang Leilei Gan CML 43 21 0 12 Jun 2020
A Survey on Causal Inference Liuyi Yao Zhixuan Chu Sheng Li Yaliang Li Jing Gao Aidong Zhang CML 62 506 0 05 Feb 2020
Causality matters in medical imaging Daniel Coelho De Castro Ian Walker Ben Glocker CML 36 343 0 17 Dec 2019
Support and Invertibility in Domain-Invariant Representations Fredrik D. Johansson David Sontag Rajesh Ranganath 58 162 0 08 Mar 2019
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves Patrick Schwab Lorenz Linhardt Stefan Bauer J. M. Buhmann W. Karlen CML OOD 64 133 0 03 Feb 2019
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 413 20,061 0 30 Oct 2017
Causal Effect Inference with Deep Latent-Variable Models Christos Louizos Uri Shalit Joris Mooij David Sontag R. Zemel Max Welling CML BDL 171 742 0 24 May 2017
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 271 729 0 12 May 2016

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