Treatment effect estimation with disentangled latent factors

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Treatment effect estimation with disentangled latent factors

29 January 2020

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Papers citing "Treatment effect estimation with disentangled latent factors"

17 / 17 papers shown

Title
Federated Instrumental Variable Analysis via Federated Generalized Method of Moments Geetika Somya Tyagi Bapi Chatterjee FedML 19 0 0 27 May 2025
Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal Inference Debo Cheng Yang Xie Ziqi Xu Jiuyong Li Lin Liu Jixue Liu Yinghao Zhang Zaiwen Feng CML BDL 55 1 0 08 Dec 2023
High Dimensional Causal Inference with Variational Backdoor Adjustment Daniel Israel Aditya Grover Guy Van den Broeck CML 51 0 0 09 Oct 2023
Linking a predictive model to causal effect estimation Jiuyong Li Lin Liu Ziqi Xu Ha Xuan Tran T. Le Jixue Liu CML 63 0 0 10 Apr 2023
Towards Learning and Explaining Indirect Causal Effects in Neural Networks Abbaavaram Gowtham Reddy Saketh Bachu Harsh Nilesh Pathak Ben Godfrey V. Balasubramanian V. Varshaneya Satya Narayanan Kar CML 69 1 0 24 Mar 2023
Instrumental Variables in Causal Inference and Machine Learning: A Survey Anpeng Wu Kun Kuang Ruoxuan Xiong Leilei Gan SyDa CML 72 7 0 12 Dec 2022
Confounder Balancing for Instrumental Variable Regression with Latent Variable Anpeng Wu Kun Kuang Ruoxuan Xiong Bo Li Leilei Gan CML 81 0 0 18 Nov 2022
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation Abbavaram Gowtham Reddy V. Balasubramanian CML 42 0 0 08 Nov 2022
Adversarial De-confounding in Individualised Treatment Effects Estimation Vinod Kumar Chauhan Soheila Molaei Marzia Hoque Tania Anshul Thakur T. Zhu David Clifton CML 46 14 0 19 Oct 2022
Long-term Causal Effects Estimation via Latent Surrogates Representation Learning Ruichu Cai Weilin Chen Zeqin Yang Shu Wan Chen Zheng Xiaoqing Yang Jiecheng Guo CML BDL 94 12 0 09 Aug 2022
Variational Temporal Deconfounder for Individualized Treatment Effect Estimation from Longitudinal Observational Data Zheng Feng M. Prosperi Jiang Bian CML 42 0 0 23 Jul 2022
Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimization Min Cheng Xinru Liao Quanlian Liu Bin Ma Jian Xu Bo Zheng CML 69 25 0 02 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 75 11 0 18 Mar 2022
$β$ -Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap Pengzhou (Abel) Wu Kenji Fukumizu CML 77 15 0 11 Oct 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 65 3 0 30 Sep 2021
Targeted VAE: Variational and Targeted Learning for Causal Inference M. Vowels Necati Cihan Camgöz Richard Bowden BDL OOD CML 34 8 0 28 Sep 2020
Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition Vincent Dorie J. Hill Uri Shalit M. Scott D. Cervone CML 261 288 0 09 Jul 2017