Learning Representations for Counterfactual Inference

12 May 2016

Papers citing "Learning Representations for Counterfactual Inference"

50 / 109 papers shown

Title
Q-function Decomposition with Intervention Semantics with Factored Action Spaces Junkyu Lee Tian Gao Elliot Nelson Miao Liu D. Bhattacharjya Songtao Lu OffRL 45 0 0 30 Apr 2025
The Estimation of Continual Causal Effect for Dataset Shifting Streams Baining Chen Yiming Zhang Yuqiao Han Ruyue Zhang Ruihuan Du Zhishuo Zhou Zhengdan Zhu Xun Liu Jiecheng Guo 125 0 0 29 Apr 2025
Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects Praharsh Nanavati Ranjitha Prasad Karthikeyan Shanmugam OOD CML 66 0 0 29 Apr 2025
TSCAN: Context-Aware Uplift Modeling via Two-Stage Training for Online Merchant Business Diagnosis Hangtao Zhang Zhe Li Kaipeng Zhang 31 0 0 26 Apr 2025
Semiparametric Counterfactual Regression Kwangho Kim OffRL 36 0 0 03 Apr 2025
Nonparametric Heterogeneous Long-term Causal Effect Estimation via Data Combination Weilin Chen Ruichu Cai Junjie Wan Zeqin Yang José Miguel Hernández-Lobato 51 1 0 26 Feb 2025
Individualised Treatment Effects Estimation with Composite Treatments and Composite Outcomes V. Chauhan Lei A. Clifton Gaurav Nigam David A. Clifton CML 63 0 0 12 Feb 2025
Stabilized Neural Prediction of Potential Outcomes in Continuous Time Konstantin Hess Stefan Feuerriegel 48 0 0 04 Oct 2024
Identifying treatment response subgroups in observational time-to-event data Vincent Jeanselme Chang Ho Yoon Fabian Falck Brian D. M. Tom Jessica Barrett OOD CML 45 0 0 06 Aug 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
Compositional Models for Estimating Causal Effects Purva Pruthi David D. Jensen CML 67 0 0 25 Jun 2024
Conformal Counterfactual Inference under Hidden Confounding Zonghao Chen Ruocheng Guo Jean-François Ton Yang Liu CML OffRL 47 2 0 20 May 2024
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning Weilin Chen Ruichu Cai Zeqin Yang Jie Qiao Yuguang Yan Zijian Li Zhifeng Hao CML 42 7 0 06 May 2024
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation Yoichi Chikahara Kansei Ushiyama 39 0 0 26 Apr 2024
C-XGBoost: A tree boosting model for causal effect estimation Niki Kiriakidou I. Livieris Christos Diou CML 31 1 0 31 Mar 2024
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects Masahiro Kato CML 39 1 0 05 Mar 2024
Defining Expertise: Applications to Treatment Effect Estimation Alihan Huyuk Qiyao Wei Alicia Curth M. Schaar CML 40 2 0 01 Mar 2024
Federated Learning for Estimating Heterogeneous Treatment Effects Disha Makhija Joydeep Ghosh Yejin Kim CML FedML 40 2 0 27 Feb 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 49 2 0 19 Dec 2023
Adversarially Balanced Representation for Continuous Treatment Effect Estimation Amirreza Kazemi Martin Ester CML OOD 35 3 0 17 Dec 2023
A Neural Framework for Generalized Causal Sensitivity Analysis Dennis Frauen F. Imrie Alicia Curth Valentyn Melnychuk Stefan Feuerriegel M. Schaar CML 31 10 0 27 Nov 2023
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 32 9 0 19 Nov 2023
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML OOD 68 2 0 16 Oct 2023
Generalizable Resource Scaling of 5G Slices using Constrained Reinforcement Learning Muhammad Sulaiman Mahdieh Ahmadi M. A. Salahuddin R. Boutaba A. Saleh 39 6 0 15 Jun 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
An Efficient Doubly-Robust Test for the Kernel Treatment Effect Diego Martinez-Taboada Aaditya Ramdas Edward H. Kennedy OOD 23 5 0 26 Apr 2023
Continual Causal Inference with Incremental Observational Data Zhixuan Chu Ruopeng Li S. Rathbun Sheng Li CML 41 14 0 03 Mar 2023
Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data Alicia Curth M. Schaar CML 10 3 0 23 Feb 2023
Domain Adaptation via Rebalanced Sub-domain Alignment Yi-Ling Liu Juncheng Dong Ziyang Jiang Ahmed Aloui Keyu Li Hunter Klein Vahid Tarokh David Carlson 34 2 0 03 Feb 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey Guanglin Zhou Shaoan Xie Guang-Yuan Hao Shiming Chen Erdun Gao Xiwei Xu Chen Wang Liming Zhu Lina Yao Anton van den Hengel AI4CE 55 11 0 29 Jan 2023
Proximal Causal Learning of Conditional Average Treatment Effects Erik Sverdrup Yifan Cui CML 28 4 0 26 Jan 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 30 1 0 16 Jan 2023
Unpacking the "Black Box" of AI in Education Nabeel Gillani R. Eynon Catherine Chiabaut Kelsey Finkel 31 58 0 31 Dec 2022
Deep Causal Learning for Robotic Intelligence Yongqian Li CML 37 5 0 23 Dec 2022
TCFimt: Temporal Counterfactual Forecasting from Individual Multiple Treatment Perspective Pengfei Xi Guifeng Wang Zhipeng Hu Yu Xiong Ming‐Fu Gong ... Runze Wu Yu-qiong Ding Tangjie Lv Changjie Fan Xiangnan Feng CML AI4TS AI4CE 18 0 0 17 Dec 2022
Counterfactual Learning with Multioutput Deep Kernels A. Caron G. Baio I. Manolopoulou BDL CML OffRL 25 1 0 20 Nov 2022
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
Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation Diego Martinez-Taboada Dino Sejdinovic CML OffRL 23 0 0 02 Nov 2022
Learning Individual Treatment Effects under Heterogeneous Interference in Networks Ziyu Zhao Yuqi Bai Kun Kuang Ruoxuan Xiong Fei Wu CML 24 6 0 25 Oct 2022
Neural Causal Models for Counterfactual Identification and Estimation K. Xia Yushu Pan Elias Bareinboim CML 43 32 0 30 Sep 2022
Moderately-Balanced Representation Learning for Treatment Effects with Orthogonality Information Yiyan Huang Cheuk Hang Leung Shumin Ma Qi Wu DongDong Wang Zhixiang Huang OOD CML 37 3 0 05 Sep 2022
Learning to Infer Counterfactuals: Meta-Learning for Estimating Multiple Imbalanced Treatment Effects Guanglin Zhou Lina Yao Xiwei Xu Chen Wang Liming Zhu OOD CML BDL 19 2 0 13 Aug 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 37 12 0 09 Aug 2022
Device-Cloud Collaborative Recommendation via Meta Controller Jiangchao Yao Feng Wang Xichen Ding Shaohu Chen Bo Han Jingren Zhou Hongxia Yang 30 17 0 07 Jul 2022
Interpretable Deep Causal Learning for Moderation Effects A. Caron G. Baio I. Manolopoulou CML OOD 23 2 0 21 Jun 2022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability Jonathan Crabbé Alicia Curth Ioana Bica M. Schaar CML 22 16 0 16 Jun 2022
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations Nabeel Seedat F. Imrie Alexis Bellot Zhaozhi Qian M. Schaar OOD CML 29 52 0 16 Jun 2022
Is More Data All You Need? A Causal Exploration Athanasios Vlontzos Hadrien Reynaud Bernhard Kainz CML 29 2 0 06 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 14 24 0 02 Jun 2022