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Learning Representations for Counterfactual Inference

12 May 2016

Papers citing "Learning Representations for Counterfactual Inference"

50 / 414 papers shown

Title
Synthetic Counterfactual Labels for Efficient Conformal Counterfactual Inference Amirmohammad Farzaneh Matteo Zecchin Osvaldo Simeone 0 0 0 04 Sep 2025
LLM-based Agents for Automated Confounder Discovery and Subgroup Analysis in Causal Inference Po-Han Lee Yu-Cheng Lin Chan-Tung Ku Chan Hsu Pei-Cing Huang Ping-Hsun Wu Yihuang Kang CML AI4CE 29 0 0 10 Aug 2025
ADT4Coupons: An Innovative Framework for Sequential Coupon Distribution in E-commerce Li Kong Bingzhe Wang Zhou Chen Suhan Hu Yuchao Ma Qi Qi Suoyuan Song Bicheng Jin OffRL 41 0 0 08 Aug 2025
Structure Maintained Representation Learning Neural Network for Causal Inference Yang Sun Wenbin Lu Yi-Hui Zhou OOD CML 38 0 0 03 Aug 2025
Personalized Treatment Effect Estimation from Unstructured Data Henri Arno Thomas Demeester CML 42 0 0 28 Jul 2025
Causality-aligned Prompt Learning via Diffusion-based Counterfactual Generation Xinshu Li Ruoyu Wang Erdun Gao Mingming Gong Lina Yao DiffM 43 0 0 26 Jul 2025
Hybrid Meta-learners for Estimating Heterogeneous Treatment Effects Zhongyuan Liang L. Laan Ahmed Alaa 61 0 0 16 Jun 2025
On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization Undral Byambadalai Tomu Hirata Tatsushi Oka Shota Yasui 69 2 0 06 Jun 2025
M-learner:A Flexible And Powerful Framework To Study Heterogeneous Treatment Effect In Mediation Model Xingyu Li Qing Liu Tony Jiang Hong Amy Xia Brian P. Hobbs Peng Wei 116 0 0 23 May 2025
A Distributionally-Robust Framework for Nuisance in Causal Effect Estimation Akira Tanimoto 94 0 0 23 May 2025
PO-Flow: Flow-based Generative Models for Sampling Potential Outcomes and Counterfactuals Dongze Wu David I. Inouye Yao Xie 85 0 0 21 May 2025
Q-function Decomposition with Intervention Semantics with Factored Action Spaces Junkyu Lee Tian Gao Elliot Nelson Miao Liu D. Bhattacharjya Songtao Lu OffRL 119 0 0 30 Apr 2025
Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects Praharsh Nanavati Ranjitha Prasad Karthikeyan Shanmugam OOD CML 145 0 0 29 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 521 0 0 29 Apr 2025
TSCAN: Context-Aware Uplift Modeling via Two-Stage Training for Online Merchant Business Diagnosis Hangtao Zhang Zhe Li Jianchao Tan 154 0 0 26 Apr 2025
Semiparametric Counterfactual Regression Kwangho Kim OffRL 165 0 0 03 Apr 2025
Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do Yoav Wald M. Goldstein Yonathan Efroni Wouter A. C. van Amsterdam Rajesh Ranganath CML 203 0 0 20 Mar 2025
KANITE: Kolmogorov-Arnold Networks for ITE estimation Eshan Mehendale Abhinav Thorat Ravi Kolla N. Pedanekar CML 173 1 0 18 Mar 2025
Federated Inverse Probability Treatment Weighting for Individual Treatment Effect Estimation Changchang Yin Hong-You Chen Wei-Lun Chao Ping Zhang CML 119 1 0 06 Mar 2025
Causal Effect Estimation under Networked Interference without Networked Unconfoundedness Assumption Weilin Chen Ruichu Cai Jie Qiao Yuguang Yan José Miguel Hernández-Lobato CML 152 0 0 27 Feb 2025
Nonparametric Heterogeneous Long-term Causal Effect Estimation via Data Combination Weilin Chen Ruichu Cai Junjie Wan Zeqin Yang José Miguel Hernández-Lobato 206 1 0 26 Feb 2025
Learning Counterfactual Outcomes Under Rank Preservation Peng Wu Haoxuan Li Chunyuan Zheng Yan Zeng Jiawei Chen Yang Liu Ruocheng Guo Jianchao Tan 134 0 0 10 Feb 2025
Orthogonal Representation Learning for Estimating Causal Quantities Valentyn Melnychuk Dennis Frauen Jonas Schweisthal Stefan Feuerriegel CML OOD BDL 176 3 0 06 Feb 2025
Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets Yuxin Wang Maresa Schröder Dennis Frauen Jonas Schweisthal Konstantin Hess Stefan Feuerriegel CML 232 5 0 16 Dec 2024
Estimating the treatment effect over time under general interference through deep learner integrated TMLE Suhan Guo Furao Shen Ni Li CML 189 0 0 06 Dec 2024
Disentangled Representation Learning for Causal Inference with Instruments Debo Cheng Jiuyong Li Lin Liu Ziqi Xu Weijia Zhang Qingbin Liu T. Le OOD CML 99 5 0 05 Dec 2024
I See, Therefore I Do: Estimating Causal Effects for Image Treatments Abhinav Thorat Ravi Kolla N. Pedanekar CML 117 2 0 28 Nov 2024
Navigating Spatial Inequities in Freight Truck Crash Severity via Counterfactual Inference in Los Angeles Yichen Wang Hao Yin Yifan Yang Chenyang Zhao Siqin Wang 94 0 0 26 Nov 2024
$C$^{2}$INet: Realizing Incremental Trajectory Prediction with Prior-Aware Continual Causal Intervention$ C $^{2}$ INet: Realizing Incremental Trajectory Prediction with Prior-Aware Continual Causal Intervention Xiaohe Li Feilong Huang Zide Fan Fangli Mou Leilei Lin Yingyan Hou Lijie Wen 150 0 0 19 Nov 2024
Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation Hechuan Wen Tong Chen Guanhua Ye Li Kheng Chai S. Sadiq Hongzhi Yin OOD 148 1 0 18 Nov 2024
Testing Generalizability in Causal Inference Daniel de Vassimon Manela Linying Yang Robin J. Evans 118 0 0 05 Nov 2024
Combining Incomplete Observational and Randomized Data for Heterogeneous Treatment Effects Dong Yao Caizhi Tang Daixin Wang Longfei Li CML 109 0 0 28 Oct 2024
DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification Xiaoxue Han Huzefa Rangwala Yue Ning BDL OOD CML 113 0 0 27 Oct 2024
Causality for Large Language Models Anpeng Wu Kun Kuang Minqin Zhu Yingrong Wang Yujia Zheng Kairong Han Yangqiu Song Guangyi Chen Leilei Gan Kun Zhang LRM 172 12 0 20 Oct 2024
DiffPO: A causal diffusion model for learning distributions of potential outcomes Yuchen Ma Valentyn Melnychuk Jonas Schweisthal Stefan Feuerriegel DiffM 202 9 0 11 Oct 2024
Are causal effect estimations enough for optimal recommendations under multitreatment scenarios? Sherly Alfonso-Sánchez Kristina P. Sendova Cristián Bravo CML 66 0 0 07 Oct 2024
Stabilized Neural Prediction of Potential Outcomes in Continuous Time Konstantin Hess Stefan Feuerriegel 240 1 0 04 Oct 2024
Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification Michael Vollenweider Manuel Schürch Chiara Rohrer Gabriele Gut Michael Krauthammer Andreas Wicki CML 156 0 0 01 Oct 2024
Optimizing Treatment Allocation in the Presence of Interference Daan Caljon Jente Van Belle Jeroen Berrevoets Wouter Verbeke 148 0 0 30 Sep 2024
Ads Supply Personalization via Doubly Robust Learning Wei Shi Chen Fu Qi Xu Sanjian Chen Jizhe Zhang Qinqin Zhu Zhigang Hua Shuang Yang OffRL 98 2 0 29 Sep 2024
Towards Representation Learning for Weighting Problems in Design-Based Causal Inference Oscar Clivio Avi Feller Chris Holmes CML OOD 94 3 0 24 Sep 2024
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm R. Teal Witter Christopher Musco 112 0 0 06 Sep 2024
Causal Rule Forest: Toward Interpretable and Precise Treatment Effect Estimation Chan Hsu Jun-Ting Wu Yihuang Kang CML 72 0 0 27 Aug 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 256 0 0 06 Aug 2024
Conformal Diffusion Models for Individual Treatment Effect Estimation and Inference Hengrui Cai Huaqing Jin Lexin Li 98 1 0 02 Aug 2024
On the Effects of Irrelevant Variables in Treatment Effect Estimation with Deep Disentanglement Ahmad Saeed Khan Erik Schaffernicht J. A. Stork CML 170 1 0 29 Jul 2024
Causal Interventional Prediction System for Robust and Explainable Effect Forecasting Zhixuan Chu Hui Ding Guang Zeng Shiyu Wang Yiming Li CML 120 2 0 29 Jul 2024
MiranDa: Mimicking the Learning Processes of Human Doctors to Achieve Causal Inference for Medication Recommendation Ziheng Wang Xinhe Li H. Momma Stefan Köpsell CML 105 0 0 23 Jul 2024
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction Undral Byambadalai Tatsushi Oka Shota Yasui CML 101 5 0 22 Jul 2024
MSCT: Addressing Time-Varying Confounding with Marginal Structural Causal Transformer for Counterfactual Post-Crash Traffic Prediction Shuang Li Ziyuan Pu Nan Zhang Duxin Chen Lu Dong Daniel J. Graham Yinhai Wang 135 0 0 19 Jul 2024