Learning Representations for Counterfactual Inference

12 May 2016

Papers citing "Learning Representations for Counterfactual Inference"

50 / 96 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 103 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 K. Zhang 31 0 0 26 Apr 2025
Semiparametric Counterfactual Regression Kwangho Kim OffRL 31 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 58 0 0 12 Feb 2025
Stabilized Neural Prediction of Potential Outcomes in Continuous Time Konstantin Hess Stefan Feuerriegel 46 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 40 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 21 0 0 29 Jul 2024
Compositional Models for Estimating Causal Effects Purva Pruthi David D. Jensen CML 65 0 0 25 Jun 2024
Conformal Counterfactual Inference under Hidden Confounding Zonghao Chen Ruocheng Guo Jean-François Ton Yang Liu CML OffRL 38 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 32 7 0 06 May 2024
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation Yoichi Chikahara Kansei Ushiyama 32 0 0 26 Apr 2024
C-XGBoost: A tree boosting model for causal effect estimation Niki Kiriakidou I. Livieris Christos Diou CML 29 1 0 31 Mar 2024
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects Masahiro Kato CML 37 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 33 2 0 27 Feb 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 38 2 0 19 Dec 2023
A Neural Framework for Generalized Causal Sensitivity Analysis Dennis Frauen F. Imrie Alicia Curth Valentyn Melnychuk Stefan Feuerriegel M. Schaar CML 26 10 0 27 Nov 2023
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 27 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 60 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 27 6 0 15 Jun 2023
An Efficient Doubly-Robust Test for the Kernel Treatment Effect Diego Martinez-Taboada Aaditya Ramdas Edward H. Kennedy OOD 18 5 0 26 Apr 2023
Continual Causal Inference with Incremental Observational Data Zhixuan Chu Ruopeng Li S. Rathbun Sheng R. Li CML 37 14 0 03 Mar 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 20 2 0 03 Feb 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey Guanglin Zhou Shaoan Xie Guang-Yuan Hao Shiming Chen Biwei Huang Xiwei Xu Chen Wang Liming Zhu Lina Yao Kun Zhang AI4CE 50 11 0 29 Jan 2023
Proximal Causal Learning of Conditional Average Treatment Effects Erik Sverdrup Yifan Cui CML 21 4 0 26 Jan 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 25 1 0 16 Jan 2023
Unpacking the "Black Box" of AI in Education Nabeel Gillani R. Eynon Catherine Chiabaut Kelsey Finkel 21 57 0 31 Dec 2022
Deep Causal Learning for Robotic Intelligence Y. Li CML 32 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 13 0 0 17 Dec 2022
Counterfactual Learning with Multioutput Deep Kernels A. Caron G. Baio I. Manolopoulou BDL CML OffRL 15 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 38 0 0 18 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 31 11 0 07 Nov 2022
Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation Diego Martinez-Taboada Dino Sejdinovic CML OffRL 19 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 22 6 0 25 Oct 2022
Neural Causal Models for Counterfactual Identification and Estimation K. Xia Yushu Pan Elias Bareinboim CML 39 31 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 29 3 0 05 Sep 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 21 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 26 17 0 07 Jul 2022
Interpretable Deep Causal Learning for Moderation Effects A. Caron G. Baio I. Manolopoulou CML OOD 19 2 0 21 Jun 2022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability Jonathan Crabbé Alicia Curth Ioana Bica M. Schaar CML 20 15 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 27 52 0 16 Jun 2022
Is More Data All You Need? A Causal Exploration Athanasios Vlontzos Hadrien Reynaud Bernhard Kainz CML 19 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
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage Alexis Bellot Anish Dhir G. Prando CML 11 11 0 29 May 2022
Robust and Agnostic Learning of Conditional Distributional Treatment Effects Nathan Kallus M. Oprescu CML OOD 35 10 0 23 May 2022
An improved neural network model for treatment effect estimation Niki Kiriakidou Christos Diou CML 45 3 0 23 May 2022
Neuroevolutionary Feature Representations for Causal Inference Michael C. Burkhart Gabriel Ruiz CML OOD 18 2 0 21 May 2022