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Learning Representations for Counterfactual Inference

12 May 2016

Papers citing "Learning Representations for Counterfactual Inference"

50 / 403 papers shown

Title
Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data Miruna Oprescu Nathan Kallus CML 65 0 0 10 Jun 2024
PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect Lokesh Nagalapatti Pranava Singhal Avishek Ghosh Sunita Sarawagi CML OOD 77 1 0 06 Jun 2024
Prediction-powered Generalization of Causal Inferences Ilker Demirel Ahmed M. Alaa Anthony Philippakis David Sontag OOD 66 8 0 05 Jun 2024
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments Jonas Schweisthal Dennis Frauen M. Schaar Stefan Feuerriegel CML 100 7 0 04 Jun 2024
Disentangled Representation via Variational AutoEncoder for Continuous Treatment Effect Estimation Ruijing Cui Jianbin Sun Bingyu He Kewei Yang Bingfeng Ge 67 0 0 04 Jun 2024
G-Transformer for Conditional Average Potential Outcome Estimation over Time Konstantin Hess Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel 113 2 0 31 May 2024
Revisiting Counterfactual Regression through the Lens of Gromov-Wasserstein Information Bottleneck Hao Yang Zexu Sun Hongteng Xu Xu Chen 105 3 0 24 May 2024
Blood Glucose Control Via Pre-trained Counterfactual Invertible Neural Networks Jingchi Jiang Rujia Shen Boran Wang Yi Guan OffRL BDL 66 1 0 23 May 2024
Conformal Counterfactual Inference under Hidden Confounding Zonghao Chen Ruocheng Guo Jean-François Ton Yang Liu CML OffRL 214 3 0 20 May 2024
Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity Analysis Daniel Csillag C. Struchiner G. Goedert OOD CML 61 2 0 15 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 79 7 0 06 May 2024
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference Haoxuan Li Chunyuan Zheng Sihao Ding Peng Wu Zhi Geng Fuli Feng Xiangnan He CML 74 10 0 30 Apr 2024
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation Yoichi Chikahara Kansei Ushiyama 58 0 0 26 Apr 2024
Neural Networks with Causal Graph Constraints: A New Approach for Treatment Effects Estimation Roger Pros Jordi Vitrià CML 90 0 0 18 Apr 2024
Causal Effect Estimation Using Random Hyperplane Tessellations Abhishek Dalvi Neil Ashtekar V. Honavar 154 0 0 16 Apr 2024
C-XGBoost: A tree boosting model for causal effect estimation Niki Kiriakidou I. Livieris Christos Diou CML 72 1 0 31 Mar 2024
Uplift Modeling Under Limited Supervision G. Panagopoulos Daniele Malitesta Fragkiskos D. Malliaros Jun Pang CML 116 0 0 28 Mar 2024
A Causal Analysis of CO2 Reduction Strategies in Electricity Markets Through Machine Learning-Driven Metalearners Iman Emtiazi Naeini Zahra Saberi Khadijeh Hassanzadeh 21 0 0 21 Mar 2024
Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects Seyedeh Baharan Khatami Harsh Parikh Haowei Chen Sudeepa Roy Babak Salimi OOD 78 1 0 17 Mar 2024
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference Krzysztof Kacprzyk Samuel Holt Jeroen Berrevoets Zhaozhi Qian M. Schaar 93 7 0 16 Mar 2024
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects Masahiro Kato CML 70 1 0 05 Mar 2024
Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects Yingrong Wang Anpeng Wu Haoxuan Li Weiming Liu Qiaowei Miao Ruoxuan Xiong Leilei Gan Kun Kuang 70 0 0 05 Mar 2024
Defining Expertise: Applications to Treatment Effect Estimation Alihan Huyuk Qiyao Wei Alicia Curth M. Schaar CML 68 2 0 01 Mar 2024
Unveiling the Potential of Robustness in Evaluating Causal Inference Models Yiyan Huang Cheuk Hang Leung Siyi Wang Yijun Li Qi Wu OOD CML 76 0 0 28 Feb 2024
Federated Learning for Estimating Heterogeneous Treatment Effects Disha Makhija Joydeep Ghosh Yejin Kim CML FedML 94 2 0 27 Feb 2024
A Perspective on Individualized Treatment Effects Estimation from Time-series Health Data Ghadeer O. Ghosheh Moritz Gögl Tingting Zhu 93 0 0 07 Feb 2024
Causal Machine Learning for Cost-Effective Allocation of Development Aid Milan Kuzmanovic Dennis Frauen Tobias Hatt Stefan Feuerriegel 111 8 0 30 Jan 2024
Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing Lokesh Nagalapatti Akshay Iyer Abir De Sunita Sarawagi CML 58 8 0 27 Jan 2024
Distributionally Robust Policy Evaluation under General Covariate Shift in Contextual Bandits Yi Guo Hao Liu Yisong Yue Anqi Liu OffRL 99 2 0 21 Jan 2024
Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social Networks Ziqiang Cui Xing Tang Yang Qiao Bowei He Liang Chen Xiuqiang He Chen Ma CML 71 0 0 12 Jan 2024
Neural Causal Abstractions K. Xia Elias Bareinboim CML NAI 103 7 0 05 Jan 2024
Is Knowledge All Large Language Models Needed for Causal Reasoning? Hengrui Cai Shengjie Liu Rui Song LRM ELM 109 13 0 30 Dec 2023
Causal Forecasting for Pricing Douglas Schultz Johannes Stephan Julian Sieber Trudie Yeh Manuel Kunz Patrick Doupe Tim Januschowski 56 2 0 23 Dec 2023
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 130 3 0 19 Dec 2023
Adversarially Balanced Representation for Continuous Treatment Effect Estimation Amirreza Kazemi Martin Ester CML OOD 83 3 0 17 Dec 2023
Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear Model Shunsuke Horii Yoichi Chikahara 56 4 0 16 Dec 2023
Adversarial Distribution Balancing for Counterfactual Reasoning Stefan Schrod Fabian H. Sinz Michael Altenbuchinger OOD CML 88 1 0 28 Nov 2023
A Neural Framework for Generalized Causal Sensitivity Analysis Dennis Frauen F. Imrie Alicia Curth Valentyn Melnychuk Stefan Feuerriegel M. Schaar CML 92 10 0 27 Nov 2023
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 79 10 0 19 Nov 2023
Causal Inference from Text: Unveiling Interactions between Variables Yuxiang Zhou Yulan He CML 65 4 0 09 Nov 2023
CATE Estimation With Potential Outcome Imputation From Local Regression Ahmed Aloui Juncheng Dong Cat P. Le Vahid Tarokh CML 38 2 0 07 Nov 2023
Estimating treatment effects from single-arm trials via latent-variable modeling Manuel Haussmann Tran Minh Son Le Viivi Halla-aho Samu Kurki Jussi Leinonen Miika Koskinen Samuel Kaski Harri Lähdesmäki CML 97 0 0 06 Nov 2023
Identifiable Contrastive Learning with Automatic Feature Importance Discovery Qi Zhang Yifei Wang Yisen Wang 70 13 0 29 Oct 2023
Optimal Transport for Treatment Effect Estimation Hao Wang Zhichao Chen Jiajun Fan Haoxuan Li Tianqiao Liu Weiming Liu Quanyu Dai Yichao Wang Zhenhua Dong Ruiming Tang OT CML 82 38 0 27 Oct 2023
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation Konstantin Hess Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel 66 16 0 26 Oct 2023
CATE Lasso: Conditional Average Treatment Effect Estimation with High-Dimensional Linear Regression Masahiro Kato Masaaki Imaizumi CML 68 2 0 25 Oct 2023
Counterfactual Prediction Under Selective Confounding Sohaib Kiani Jared Barton Jon Sushinsky Lynda Heimbach Bo Luo CML 100 1 0 21 Oct 2023
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML OOD 205 2 0 16 Oct 2023
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder Ziqi Xu Debo Cheng Jiuyong Li Jixue Liu Lin Liu Kui Yu CML 74 9 0 03 Oct 2023
Towards Causal Foundation Model: on Duality between Causal Inference and Attention Jiaqi Zhang Joel Jennings Agrin Hilmkil Nick Pawlowski Cheng Zhang Chao Ma CML 112 14 0 01 Oct 2023