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Learning Representations for Counterfactual Inference

12 May 2016

Papers citing "Learning Representations for Counterfactual Inference"

50 / 414 papers shown

Title
Estimating Individual Treatment Effects with Time-Varying Confounders Ruoqi Liu Changchang Yin Ping Zhang CML 157 29 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 141 4 0 22 Aug 2020
Long-Term Effect Estimation with Surrogate Representation Lu Cheng Ruocheng Guo Huan Liu CML 96 20 0 19 Aug 2020
Estimating Causal Effects with the Neural Autoregressive Density Estimator Sergio Garrido S. Borysov Jeppe Rich Francisco Câmara Pereira CML 112 8 0 17 Aug 2020
On Learning Language-Invariant Representations for Universal Machine Translation Hao Zhao Junjie Hu Andrej Risteski 119 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 78 9 0 01 Aug 2020
An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models Catarina Moreira Yu-Liang Chou M. Velmurugan Chun Ouyang Prerna Agarwal P. Bruza 147 60 0 21 Jul 2020
Causal Inference using Gaussian Processes with Structured Latent Confounders Sam Witty Kenta Takatsu David D. Jensen Vikash K. Mansinghka CML 173 19 0 14 Jul 2020
A unified survey of treatment effect heterogeneity modeling and uplift modeling Weijia Zhang Jiuyong Li Lin Liu CML 158 65 0 14 Jul 2020
On Linear Identifiability of Learned Representations Geoffrey Roeder Luke Metz Diederik P. Kingma CML 174 88 0 01 Jul 2020
Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models Andrew Jesson Sören Mindermann Uri Shalit Y. Gal CML 156 74 0 01 Jul 2020
Adversarial representation learning for synthetic replacement of private attributes John Martinsson Edvin Listo Zec D. Gillblad Olof Mogren PICV 128 8 0 14 Jun 2020
Learning Decomposed Representation for Counterfactual Inference Anpeng Wu Kun Kuang Junkun Yuan Bo Li Jianrong Tao Qiang Zhu Yueting Zhuang Leilei Gan CML 116 22 0 12 Jun 2020
Regret Minimization for Causal Inference on Large Treatment Space Akira Tanimoto Tomoya Sakai Takashi Takenouchi H. Kashima CML 95 10 0 10 Jun 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 99 22 0 03 Jun 2020
CausaLM: Causal Model Explanation Through Counterfactual Language Models Amir Feder Nadav Oved Uri Shalit Roi Reichart CML LRM 267 168 0 27 May 2020
Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation Shonosuke Harada H. Kashima CML 47 3 0 11 May 2020
Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates Katherine A. Keith David D. Jensen Brendan O'Connor CML 131 120 0 01 May 2020
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks Ankit Sharma Garima Gupta Ranjitha Prasad Arnab Chatterjee Lovekesh Vig Gautam M. Shroff CML 74 7 0 28 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 74 2 0 21 Apr 2020
Causality-aware counterfactual confounding adjustment for feature representations learned by deep models E. C. Neto AI4CE OOD BDL CML 86 2 0 20 Apr 2020
Estimating Individual Treatment Effects through Causal Populations Identification Céline Beji Michaël Bon Florian Yger Jamal Atif CML 52 3 0 10 Apr 2020
Learning Latent Causal Structures with a Redundant Input Neural Network Jonathan D. Young Bryan Andrews G. Cooper Xinghua Lu CML 53 8 0 29 Mar 2020
ParKCa: Causal Inference with Partially Known Causes Raquel Y. S. Aoki Martin Ester CML 151 6 0 17 Mar 2020
Optimizing Medical Treatment for Sepsis in Intensive Care: from Reinforcement Learning to Pre-Trial Evaluation Luchen Li I. Albert-Smet Aldo A. Faisal OffRL 89 11 0 13 Mar 2020
Adversarial Machine Learning: Bayesian Perspectives D. Insua Roi Naveiro Víctor Gallego Jason Poulos AAML 88 29 0 07 Mar 2020
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks Ioana Bica James Jordon M. Schaar CML 162 109 0 27 Feb 2020
Off-Policy Evaluation and Learning for External Validity under a Covariate Shift Masahiro Kato Masatoshi Uehara Shota Yasui OffRL 142 54 0 26 Feb 2020
MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models Imke Mayer Julie Josse Félix Raimundo Jean-Philippe Vert CML 96 12 0 25 Feb 2020
Causal Inference under Networked Interference and Intervention Policy Enhancement Yunpu Ma Volker Tresp CML 104 43 0 20 Feb 2020
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations Ioana Bica Ahmed Alaa James Jordon M. Schaar BDL CML 126 193 0 10 Feb 2020
A Survey on Causal Inference Liuyi Yao Zhixuan Chu Sheng Li Yaliang Li Jing Gao Aidong Zhang CML 180 549 0 05 Feb 2020
Treatment effect estimation with disentangled latent factors Weijia Zhang Lin Liu Jiuyong Li CML 156 95 0 29 Jan 2020
Causal query in observational data with hidden variables Debo Cheng Jiuyong Li Lin Liu Jixue Liu Kui Yu T. Le CML 118 11 0 28 Jan 2020
On the Fairness of Randomized Trials for Recommendation with Heterogeneous Demographics and Beyond Zifeng Wang Xi Chen Rui Wen Shao-Lun Huang 176 1 0 25 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 228 105 0 21 Jan 2020
The Counterfactual $χ$ -GAN A. Averitt Natnicha Vanitchanant Rajesh Ranganath A. Perotte CML BDL 68 8 0 09 Jan 2020
Artificial Intelligence for Social Good: A Survey Zheyuan Ryan Shi Claire Wang Fei Fang AI4TS 171 87 0 07 Jan 2020
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data Ruocheng Guo Jundong Li Huan Liu CML OffRL 122 21 0 22 Dec 2019
Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation Zichen Zhang Qingfeng Lan Lei Ding Yue Wang Negar Hassanpour Russell Greiner BDL CML 89 9 0 19 Dec 2019
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population Ankit Sharma Garima Gupta Ranjitha Prasad Arnab Chatterjee Lovekesh Vig Gautam M. Shroff OOD 150 12 0 09 Dec 2019
Triply Robust Off-Policy Evaluation Anqi Liu Hao Liu Anima Anandkumar Yisong Yue OffRL 111 11 0 13 Nov 2019
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming Yura N. Perov L. Graham Kostis Gourgoulias Jonathan G. Richens Ciarán M. Gilligan-Lee Adam Baker Saurabh Johri LRM 146 17 0 17 Oct 2019
Optimising Individual-Treatment-Effect Using Bandits Jeroen Berrevoets Sam Verboven Wouter Verbeke CML 32 3 0 16 Oct 2019
Estimation of Bounds on Potential Outcomes For Decision Making Maggie Makar Fredrik D. Johansson John Guttag David Sontag 67 1 0 10 Oct 2019
Conditional out-of-sample generation for unpaired data using trVAE M. Lotfollahi Mohsen Naghipourfar Fabian J. Theis F. A. Wolf GAN ViT DRL 165 20 0 04 Oct 2019
Representation Learning for Electronic Health Records W. Weng Peter Szolovits 94 20 0 19 Sep 2019
Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models Yuta Saito Shota Yasui OOD CML 66 8 0 11 Sep 2019
Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective Tom Everitt Marcus Hutter Ramana Kumar Victoria Krakovna 244 107 0 13 Aug 2019
Quantifying Error in the Presence of Confounders for Causal Inference Rathin Desai Amit Sharma CML 35 0 0 10 Jul 2019