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Adapting Neural Networks for the Estimation of Treatment Effects

5 June 2019

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Papers citing "Adapting Neural Networks for the Estimation of Treatment Effects"

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Title
Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects Naoufal Acharki Ramiro Lugo A. Bertoncello Josselin Garnier CML 70 13 0 29 May 2022
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage Alexis Bellot Anish Dhir G. Prando CML 63 11 0 29 May 2022
Average Adjusted Association: Efficient Estimation with High Dimensional Confounders S. Jun S. Lee 79 1 0 27 May 2022
An improved neural network model for treatment effect estimation Niki Kiriakidou Christos Diou CML 87 3 0 23 May 2022
Robust and Agnostic Learning of Conditional Distributional Treatment Effects Nathan Kallus Miruna Oprescu OOD CML 122 12 0 23 May 2022
Causal Inference from Small High-dimensional Datasets Raquel Y. S. Aoki Martin Ester CML 59 4 0 19 May 2022
Multiple Domain Causal Networks Tianhui Zhou IV WilliamE.Carson M. H. Klein David Carlson CML 32 0 0 13 May 2022
Toward Data-Driven Digital Therapeutics Analytics: Literature Review and Research Directions Uichin Lee Gyuwon Jung Eun-Yeol Ma Jinsan Kim Heepyung Kim Jumabek Alikhanov Youngtae Noh Heeyoung Kim 26 21 0 04 May 2022
Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions Andrew Jesson A. Douglas P. Manshausen Maelys Solal N. Meinshausen P. Stier Y. Gal Uri Shalit CML 94 26 0 21 Apr 2022
Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI J. Durso-Finley Jean-Pierre Falet Brennan Nichyporuk Douglas L. Arnold Tal Arbel AI4CE 31 9 0 01 Apr 2022
Calibration Error for Heterogeneous Treatment Effects Yizhe Xu Steve Yadlowsky 51 12 0 24 Mar 2022
TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations Haoxuan Li Yan Lyu Chunyuan Zheng Peng Wu 98 45 0 19 Mar 2022
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies Shachi Deshpande Kaiwen Wang Dhruv Sreenivas Zheng Li Volodymyr Kuleshov CML SyDa 75 11 0 18 Mar 2022
Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation Kan Chen Qishuo Yin Q. Long CML 68 5 0 07 Mar 2022
Estimating average causal effects from patient trajectories Dennis Frauen Tobias Hatt Valentyn Melnychuk Stefan Feuerriegel OOD CML 95 25 0 02 Mar 2022
Neural Score Matching for High-Dimensional Causal Inference Oscar Clivio Fabian Falck B. Lehmann George Deligiannidis Chris Holmes CML 66 8 0 01 Mar 2022
Off-Policy Evaluation with Policy-Dependent Optimization Response Wenshuo Guo Michael I. Jordan Angela Zhou CML OffRL 50 3 0 25 Feb 2022
Partial Identification with Noisy Covariates: A Robust Optimization Approach Wenshuo Guo Mingzhang Yin Yixin Wang Michael I. Jordan 187 19 0 22 Feb 2022
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 99 76 0 21 Feb 2022
A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics M. Vowels S. Akbari Necati Cihan Camgöz Richard Bowden 56 4 0 18 Feb 2022
Targeted-BEHRT: Deep learning for observational causal inference on longitudinal electronic health records Shishir Rao M. Mamouei G. Salimi-Khorshidi Yikuan Li R. Ramakrishnan A. Hassaine D. Canoy K. Rahimi OOD CML 61 22 0 07 Feb 2022
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation Yi-Fan Zhang Hanlin Zhang Zachary Chase Lipton Li Erran Li Eric P. Xing OODD 115 30 0 02 Feb 2022
Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance Gabriel Okasa CML 51 6 0 30 Jan 2022
Individual Treatment Effect Estimation Through Controlled Neural Network Training in Two Stages Naveen Nair Karthik S. Gurumoorthy Dinesh Mandalapu CML 39 4 0 21 Jan 2022
Multi-treatment Effect Estimation from Biomedical Data Raquel Y. S. Aoki Yizhou Chen M. Ester 68 0 0 14 Dec 2021
Enhancing Counterfactual Classification via Self-Training Ruijiang Gao Max Biggs Wei-Ju Sun Ligong Han CML OffRL 200 6 0 08 Dec 2021
Variational Auto-Encoder Architectures that Excel at Causal Inference Negar Hassanpour Russell Greiner BDL CML 49 3 0 11 Nov 2021
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data Andrew Jesson P. Tigas Joost R. van Amersfoort Andreas Kirsch Uri Shalit Y. Gal CML 109 32 0 03 Nov 2021
Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific Andrew Jesson P. Manshausen A. Douglas D. Watson‐Parris Y. Gal P. Stier AI4Cl 129 7 0 28 Oct 2021
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Alicia Curth Changhee Lee M. Schaar CML 70 30 0 26 Oct 2021
Causal Effect Estimation using Variational Information Bottleneck Zhenyu Lu Yurong Cheng Mingjun Zhong G. Stoian Ye Yuan Guoren Wang CML 29 4 0 26 Oct 2021
$β$ -Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap Pengzhou (Abel) Wu Kenji Fukumizu CML 77 15 0 11 Oct 2021
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests Victor Chernozhukov Whitney Newey Victor Quintas-Martinez Vasilis Syrgkanis CML 93 40 0 06 Oct 2021
Estimating Potential Outcome Distributions with Collaborating Causal Networks Tianhui Zhou William E Carson IV David Carlson CML 208 8 0 04 Oct 2021
Algorithm Fairness in AI for Medicine and Healthcare Richard J. Chen Tiffany Y. Chen Jana Lipkova Judy J. Wang Drew F. K. Williamson Ming Y. Lu S. Sahai Faisal Mahmood FaML 141 47 0 01 Oct 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 65 3 0 30 Sep 2021
Heterogeneous Treatment Effect Estimation using machine learning for Healthcare application: tutorial and benchmark Yaobin Ling Pulakesh Upadhyaya Luyao Chen Xiaoqian Jiang Yejin Kim CML 167 21 0 27 Sep 2021
Estimating Categorical Counterfactuals via Deep Twin Networks Athanasios Vlontzos Bernhard Kainz Ciarán M. Gilligan-Lee OOD CML BDL 113 17 0 04 Sep 2021
The Causal-Neural Connection: Expressiveness, Learnability, and Inference K. Xia Kai-Zhan Lee Yoshua Bengio Elias Bareinboim CML 81 111 0 02 Jul 2021
Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge Abhin Shah Karthikeyan Shanmugam Kartik Ahuja CML 69 13 0 22 Jun 2021
Neural Networks for Partially Linear Quantile Regression Qixian Zhong Jane-ling Wang 408 14 0 11 Jun 2021
On Inductive Biases for Heterogeneous Treatment Effect Estimation Alicia Curth M. Schaar CML 193 84 0 07 Jun 2021
Causal Effect Inference for Structured Treatments Jean Kaddour Yuchen Zhu Qi Liu Matt J. Kusner Ricardo M. A. Silva CML 262 51 0 03 Jun 2021
Matched sample selection with GANs for mitigating attribute confounding Chandan Singh Guha Balakrishnan Pietro Perona GAN 69 6 0 24 Mar 2021
Robust Orthogonal Machine Learning of Treatment Effects Yiyan Huang Cheuk Hang Leung Qi Wu Xing Yan OOD CML 54 0 0 22 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 61 2 0 13 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
A Critical Look at the Consistency of Causal Estimation With Deep Latent Variable Models Severi Rissanen Pekka Marttinen CML 183 28 0 12 Feb 2021
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms Alicia Curth M. Schaar CML 181 149 0 26 Jan 2021