Treatment effect estimation with disentangled latent factors

Treatment effect estimation with disentangled latent factors

29 January 2020

Papers citing "Treatment effect estimation with disentangled latent factors"

18 / 18 papers shown

Title
Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning Ruichu Cai Junjie Wan Weilin Chen Zeqin Yang Zijian Li Peng Zhen Jiecheng Guo CML 59 1 0 08 May 2025
Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal Inference in Networks Xiaojing Du Feiyu Yang Wentao Gao Xiongren Chen CML 37 1 0 13 Sep 2024
On the Effects of Irrelevant Variables in Treatment Effect Estimation with Deep Disentanglement Ahmad Saeed Khan Erik Schaffernicht J. A. Stork CML 39 0 0 29 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 32 0 0 04 Jun 2024
Adversarially Balanced Representation for Continuous Treatment Effect Estimation Amirreza Kazemi Martin Ester CML OOD 40 3 0 17 Dec 2023
High Dimensional Causal Inference with Variational Backdoor Adjustment Daniel Israel Aditya Grover Mathias Niepert CML 13 0 0 09 Oct 2023
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation V. Chauhan Jiandong Zhou Ghadeer O. Ghosheh Soheila Molaei David A. Clifton 30 8 0 25 May 2023
Linking a predictive model to causal effect estimation Jiuyong Li Lin Liu Ziqi Xu Ha Xuan Tran T. Le Jixue Liu CML 31 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 31 0 0 24 Mar 2023
Confounder Balancing for Instrumental Variable Regression with Latent Variable Anpeng Wu Kun Kuang Ruoxuan Xiong Bo Li Fei Wu CML 40 0 0 18 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 36 11 0 07 Nov 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 40 12 0 09 Aug 2022
A Causal Research Pipeline and Tutorial for Psychologists and Social Scientists M. Vowels CML 32 2 0 10 Jun 2022
Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimization Min Cheng Xinru Liao Quanlian Liu Bin Ma Jian Xu Bo Zheng CML 21 24 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 16 11 0 18 Mar 2022
$β$ -Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap Pengzhou (Abel) Wu Kenji Fukumizu CML 35 14 0 11 Oct 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 30 3 0 30 Sep 2021
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 232 719 0 12 May 2016