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Learning Representations for Counterfactual Inference

12 May 2016

Papers citing "Learning Representations for Counterfactual Inference"

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Title
Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap Alexander DÁmour Alexander M. Franks CML 48 10 0 12 Apr 2021
Matched sample selection with GANs for mitigating attribute confounding Chandan Singh Guha Balakrishnan Pietro Perona GAN 69 6 0 24 Mar 2021
NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments S. Parbhoo Stefan Bauer Patrick Schwab CML BDL 60 16 0 20 Mar 2021
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments Lizhen Nie Mao Ye Qiang Liu D. Nicolae CML 77 71 0 14 Mar 2021
Treatment Effect Estimation using Invariant Risk Minimization Abhin Shah Kartik Ahuja Karthikeyan Shanmugam Dennis L. Wei Kush R. Varshney Amit Dhurandhar CML OOD 56 2 0 13 Mar 2021
Limitations of Post-Hoc Feature Alignment for Robustness Collin Burns Jacob Steinhardt OOD 97 23 0 10 Mar 2021
Size-Invariant Graph Representations for Graph Classification Extrapolations Beatrice Bevilacqua Yangze Zhou Bruno Ribeiro OOD 135 110 0 08 Mar 2021
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression Junhyung Park Uri Shalit Bernhard Schölkopf Krikamol Muandet CML 104 33 0 16 Feb 2021
Shrinkage Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation A. Caron G. Baio I. Manolopoulou CML 73 16 0 12 Feb 2021
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge Trent Kyono Ioana Bica Zhaozhi Qian Mihaela van der Schaar OOD CML 20 7 0 11 Feb 2021
Generating Synthetic Text Data to Evaluate Causal Inference Methods Zach Wood-Doughty I. Shpitser Mark Dredze SyDa CML 60 11 0 10 Feb 2021
Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference Koh Takeuchi Ryo Nishida Hisashi Kashima Masaki Onishi CML 21 4 0 08 Feb 2021
Learning Matching Representations for Individualized Organ Transplantation Allocation Can Xu Ahmed Alaa Ioana Bica B. Ershoff M. Cannesson M. Schaar OOD 42 7 0 28 Jan 2021
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms Alicia Curth M. Schaar CML 181 149 0 26 Jan 2021
Estimating Average Treatment Effects via Orthogonal Regularization Tobias Hatt Stefan Feuerriegel CML 236 36 0 21 Jan 2021
Model Compression for Domain Adaptation through Causal Effect Estimation Guy Rotman Amir Feder Roi Reichart CML 77 7 0 18 Jan 2021
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding Pengzhou (Abel) Wu Kenji Fukumizu CML 89 13 0 17 Jan 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 306 500 0 31 Dec 2020
CAMTA: Causal Attention Model for Multi-touch Attribution Sachin Kumar Garima Gupta Ranjitha Prasad Arnab Chatterjee Lovekesh Vig Gautam M. Shroff CML HAI 35 10 0 21 Dec 2020
Fundamental Limits and Tradeoffs in Invariant Representation Learning Han Zhao Chen Dan Bryon Aragam Tommi Jaakkola Geoffrey J. Gordon Pradeep Ravikumar FaML 90 45 0 19 Dec 2020
Treatment Targeting by AUUC Maximization with Generalization Guarantees Artem Betlei Eustache Diemert Massih-Reza Amini CML 57 5 0 17 Dec 2020
The Causal Learning of Retail Delinquency Yiyan Huang Cheuk Hang Leung Xing Yan Qi Wu Nanbo Peng DongDong Wang Zhixiang Huang CML 60 8 0 17 Dec 2020
Causality-Aware Neighborhood Methods for Recommender Systems Masahiro Sato S. Takemori Janmajay Singh Qian Zhang BDL CML 16 7 0 17 Dec 2020
Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models Dong Wang Yuewei Yang Chenyang Tao Zhe Gan Liqun Chen Fanjie Kong Ricardo Henao Lawrence Carin 57 0 0 06 Dec 2020
Balance Regularized Neural Network Models for Causal Effect Estimation Mehrdad Farajtabar Andrew Lee Yuanjian Feng Vishal Gupta Peter Dolan Harish Chandran M. Szummer CML 39 6 0 23 Nov 2020
Confounding Feature Acquisition for Causal Effect Estimation Shirly Wang S. Yi Shalmali Joshi Marzyeh Ghassemi CML 33 2 0 17 Nov 2020
Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners E. C. Neto OOD CML 61 6 0 09 Nov 2020
Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks Minshuo Chen Hao Liu Wenjing Liao T. Zhao CML OOD OffRL 36 7 0 03 Nov 2020
Adapting Neural Networks for Uplift Models Mouloud Belbahri Olivier Gandouet Ghaith Kazma 43 11 0 30 Oct 2020
DeepRite: Deep Recurrent Inverse TreatmEnt Weighting for Adjusting Time-varying Confounding in Modern Longitudinal Observational Data Yanbo Xu Cao Xiao Jimeng Sun BDL OOD CML 23 1 0 28 Oct 2020
Counterfactual Representation Learning with Balancing Weights Serge Assaad Shuxi Zeng Chenyang Tao Shounak Datta Nikhil Mehta Ricardo Henao Fan Li Lawrence Carin CML OOD 168 65 0 23 Oct 2020
Poincare: Recommending Publication Venues via Treatment Effect Estimation Ryoma Sato M. Yamada H. Kashima CML 42 2 0 19 Oct 2020
Double Robust Representation Learning for Counterfactual Prediction Shuxi Zeng Serge Assaad Chenyang Tao Shounak Datta Lawrence Carin Fan Li OOD CML 55 6 0 15 Oct 2020
GraphITE: Estimating Individual Effects of Graph-structured Treatments Shonosuke Harada H. Kashima CML 97 23 0 29 Sep 2020
Learning from eXtreme Bandit Feedback Romain Lopez Inderjit S. Dhillon Michael I. Jordan OffRL 91 25 0 27 Sep 2020
Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference Galen Cassebeer Weld Peter West M. Glenski David Arbour Ryan Rossi Tim Althoff CML 99 20 0 21 Sep 2020
Estimating Individual Treatment Effects using Non-Parametric Regression Models: a Review A. Caron G. Baio I. Manolopoulou CML 91 56 0 14 Sep 2020
Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback Zifeng Wang Xi Chen Rui Wen Shao-Lun Huang E. Kuruoglu Yefeng Zheng BDL CML OffRL 70 84 0 06 Sep 2020
BLOB : A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals Otmane Sakhi Stephen Bonner D. Rohde Flavian Vasile 94 37 0 28 Aug 2020
Estimating Individual Treatment Effects with Time-Varying Confounders Ruoqi Liu Changchang Yin Ping Zhang CML 90 27 0 27 Aug 2020
Hi-CI: Deep Causal Inference in High Dimensions Ankit Sharma Garima Gupta Ranjitha Prasad Arnab Chatterjee Lovekesh Vig Gautam M. Shroff BDL CML 61 4 0 22 Aug 2020
Long-Term Effect Estimation with Surrogate Representation Lu Cheng Ruocheng Guo Huan Liu CML 44 20 0 19 Aug 2020
Estimating Causal Effects with the Neural Autoregressive Density Estimator Sergio Garrido S. Borysov Jeppe Rich Francisco Câmara Pereira CML 42 7 0 17 Aug 2020
On Learning Language-Invariant Representations for Universal Machine Translation Hao Zhao Junjie Hu Andrej Risteski 103 8 0 11 Aug 2020
A Causal Lens for Peeking into Black Box Predictive Models: Predictive Model Interpretation via Causal Attribution A. Khademi Vasant Honavar CML 39 9 0 01 Aug 2020
An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models Catarina Moreira Yu-Liang Chou M. Velmurugan Chun Ouyang Renuka Sindhgatta P. Bruza 114 58 0 21 Jul 2020
Causal Inference using Gaussian Processes with Structured Latent Confounders Sam Witty Kenta Takatsu David D. Jensen Vikash K. Mansinghka CML 135 19 0 14 Jul 2020
A unified survey of treatment effect heterogeneity modeling and uplift modeling Weijia Zhang Jiuyong Li Lin Liu CML 83 60 0 14 Jul 2020
On Linear Identifiability of Learned Representations Geoffrey Roeder Luke Metz Diederik P. Kingma CML 70 85 0 01 Jul 2020
Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models Andrew Jesson Sören Mindermann Uri Shalit Y. Gal CML 66 74 0 01 Jul 2020