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Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning

12 June 2017

Papers citing "Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning"

41 / 191 papers shown

Title
Towards optimal doubly robust estimation of heterogeneous causal effects Edward H. Kennedy CML 196 328 0 29 Apr 2020
Learning Continuous Treatment Policy and Bipartite Embeddings for Matching with Heterogeneous Causal Effects Will Y. Zou S. Shyam Michael Mui Mingshi Wang Jan Pedersen Zoubin Ghahramani CML 53 2 0 21 Apr 2020
Heterogeneous Causal Learning for Effectiveness Optimization in User Marketing Will Y. Zou Shuyang Du James Lee Jan Pedersen CML 26 7 0 21 Apr 2020
ParKCa: Causal Inference with Partially Known Causes Raquel Y. S. Aoki Martin Ester CML 70 5 0 17 Mar 2020
CausalML: Python Package for Causal Machine Learning Huigang Chen Totte Harinen Jeong-Yoon Lee Mike Yung Zhenyu Zhao CML 71 114 0 25 Feb 2020
Causal Inference under Networked Interference and Intervention Policy Enhancement Yunpu Ma Volker Tresp CML 88 41 0 20 Feb 2020
Minimax Optimal Nonparametric Estimation of Heterogeneous Treatment Effects Zijun Gao Yanjun Han CML 87 16 0 15 Feb 2020
A Survey on Causal Inference Liuyi Yao Zhixuan Chu Sheng Li Yaliang Li Jing Gao Aidong Zhang CML 123 516 0 05 Feb 2020
Generating Digital Twins with Multiple Sclerosis Using Probabilistic Neural Networks J. Walsh Aaron M. Smith Y. Pouliot David Li-Bland A. Loukianov Charles K. Fisher AI4CE 41 29 0 04 Feb 2020
Treatment effect estimation with disentangled latent factors Weijia Zhang Lin Liu Jiuyong Li CML 99 89 0 29 Jan 2020
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects Fredrik D. Johansson Uri Shalit Nathan Kallus David Sontag CML OOD 128 100 0 21 Jan 2020
A Loss-Function for Causal Machine-Learning I-Sheng Yang CML OOD 16 1 0 02 Jan 2020
Estimation and Validation of Ratio-based Conditional Average Treatment Effects Using Observational Data Steve Yadlowsky Fabio Pellegrini F. Lionetto S. Braune L. Tian CML 16 16 0 15 Dec 2019
Response Transformation and Profit Decomposition for Revenue Uplift Modeling R. M. Gubela Stefan Lessmann S. Jaroszewicz OffRL 62 51 0 20 Nov 2019
Optimal Experimental Design for Staggered Rollouts Ruoxuan Xiong Susan Athey Mohsen Bayati Guido Imbens 65 39 0 09 Nov 2019
Group Average Treatment Effects for Observational Studies D. Jacob CML 82 20 0 07 Nov 2019
Estimation of Bounds on Potential Outcomes For Decision Making Maggie Makar Fredrik D. Johansson John Guttag David Sontag 27 1 0 10 Oct 2019
Affordable Uplift: Supervised Randomization in Controlled Experiments Johannes Haupt D. Jacob R. M. Gubela Stefan Lessmann 92 5 0 01 Oct 2019
Estimation of Personalized Heterogeneous Treatment Effects Using Concatenation and Augmentation of Feature Vectors Lev V. Utkin M. V. Kots V. Chukanov CML 27 1 0 09 Sep 2019
Uplift Modeling for Multiple Treatments with Cost Optimization Zhenyu Zhao Totte Harinen 40 49 0 14 Aug 2019
Linear Aggregation in Tree-based Estimators Sören R. Künzel Theo Saarinen Edward W. Liu Jasjeet Sekhon 141 10 0 15 Jun 2019
Identify treatment effect patterns for personalised decisions Jiuyong Li Lin Liu Yizhao Han Saisai Ma T. Le Jixue Liu CML 32 1 0 14 Jun 2019
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments Vasilis Syrgkanis Victor Lei Miruna Oprescu Maggie Hei Keith Battocchi Greg Lewis CML 50 73 0 24 May 2019
Learning When-to-Treat Policies Xinkun Nie Emma Brunskill Stefan Wager CML OffRL 82 92 0 23 May 2019
Experimental Evaluation of Individualized Treatment Rules Kosuke Imai Michael Lingzhi Li 65 39 0 14 May 2019
Synthetic learner: model-free inference on treatments over time Davide Viviano Jelena Bradic CML 92 20 0 02 Apr 2019
Machine Learning Methods Economists Should Know About Susan Athey Guido Imbens 98 685 0 24 Mar 2019
Classifying Treatment Responders Under Causal Effect Monotonicity Nathan Kallus CML 192 16 0 14 Feb 2019
Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding Muhammad Osama Dave Zachariah Thomas B. Schon 33 8 0 28 Jan 2019
Orthogonal Statistical Learning Dylan J. Foster Vasilis Syrgkanis 159 174 0 25 Jan 2019
Machine Learning Analysis of Heterogeneity in the Effect of Student Mindset Interventions Fredrik D. Johansson 8 1 0 14 Nov 2018
Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding Nathan Kallus Xiaojie Mao Angela Zhou CML 88 94 0 05 Oct 2018
Transfer Learning for Estimating Causal Effects using Neural Networks Sören R. Künzel Bradly C. Stadie N. Vemuri V. Ramakrishnan Jasjeet Sekhon Pieter Abbeel CML 49 32 0 23 Aug 2018
Local Linear Forests R. Friedberg J. Tibshirani Susan Athey Stefan Wager 157 92 0 30 Jul 2018
Improving pairwise comparison models using Empirical Bayes shrinkage Stephen Ragain A. Peysakhovich J. Ugander 48 6 0 24 Jul 2018
Representation Balancing MDPs for Off-Policy Policy Evaluation Yao Liu Omer Gottesman Aniruddh Raghu Matthieu Komorowski A. Faisal Finale Doshi-Velez Emma Brunskill OffRL 70 75 0 23 May 2018
Confounding-Robust Policy Improvement Nathan Kallus Angela Zhou CML OffRL 354 153 0 22 May 2018
Uplift Modeling from Separate Labels Ikko Yamane Florian Yger Jamal Atif Masashi Sugiyama 89 21 0 14 Mar 2018
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training Nathan Kallus CML OOD 81 77 0 15 Feb 2018
Quasi-Oracle Estimation of Heterogeneous Treatment Effects Xinkun Nie Stefan Wager CML 231 658 0 13 Dec 2017
Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition Vincent Dorie J. Hill Uri Shalit M. Scott D. Cervone CML 283 288 0 09 Jul 2017