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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"

22 / 222 papers shown

Title
Estimating Average Treatment Effects via Orthogonal Regularization Tobias Hatt Stefan Feuerriegel CML 239 36 0 21 Jan 2021
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding Pengzhou (Abel) Wu Kenji Fukumizu CML 98 13 0 17 Jan 2021
The Causal Learning of Retail Delinquency Yiyan Huang Cheuk Hang Leung Xing Yan Qi Wu Nanbo Peng DongDong Wang Zhixiang Huang CML 68 8 0 17 Dec 2020
RealCause: Realistic Causal Inference Benchmarking Brady Neal Chin-Wei Huang Sunand Raghupathi CML ELM 72 34 0 30 Nov 2020
Invariant Representation Learning for Treatment Effect Estimation Claudia Shi Victor Veitch David M. Blei OOD CML 47 31 0 24 Nov 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 46 6 0 23 Nov 2020
Representation Learning for Integrating Multi-domain Outcomes to Optimize Individualized Treatments Yuan Chen D. Zeng Tianchen Xu Yuanjia Wang AI4CE 46 3 0 30 Oct 2020
Adapting Neural Networks for Uplift Models Mouloud Belbahri Olivier Gandouet Ghaith Kazma 48 11 0 30 Oct 2020
Efficient Balanced Treatment Assignments for Experimentation David Arbour Drew Dimmery Anup B. Rao 37 7 0 21 Oct 2020
How and Why to Use Experimental Data to Evaluate Methods for Observational Causal Inference A. Gentzel Purva Pruthi David D. Jensen CML 67 18 0 06 Oct 2020
GraphITE: Estimating Individual Effects of Graph-structured Treatments Shonosuke Harada H. Kashima CML 97 23 0 29 Sep 2020
Targeted VAE: Variational and Targeted Learning for Causal Inference M. Vowels Necati Cihan Camgöz Richard Bowden BDL OOD CML 34 8 0 28 Sep 2020
Sufficient Dimension Reduction for Average Causal Effect Estimation Debo Cheng Jiuyong Li Lin Liu Jixue Liu CML 43 15 0 14 Sep 2020
Estimating Individual Treatment Effects with Time-Varying Confounders Ruoqi Liu Changchang Yin Ping Zhang CML 90 27 0 27 Aug 2020
Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models Andrew Jesson Sören Mindermann Uri Shalit Y. Gal CML 73 74 0 01 Jul 2020
Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains James Bannon Bradford T. Windsor Wenbo Song Tao Li CML OOD OffRL 73 20 0 03 Jun 2020
Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online Emaad Manzoor George H. Chen Dokyun Lee Michael D. Smith 24 8 0 01 Jun 2020
Estimating Treatment Effects with Observed Confounders and Mediators Shantanu Gupta Zachary Chase Lipton David Benjamin Childers CML 56 17 0 26 Mar 2020
ParKCa: Causal Inference with Partially Known Causes Raquel Y. S. Aoki Martin Ester CML 56 5 0 17 Mar 2020
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks Ioana Bica James Jordon M. Schaar CML 90 106 0 27 Feb 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 122 100 0 21 Jan 2020
Learning Interpretable Models with Causal Guarantees Carolyn Kim Osbert Bastani FaML OOD CML 75 17 0 24 Jan 2019