On Measurement Bias in Causal Inference

15 March 2012

Papers citing "On Measurement Bias in Causal Inference"

46 / 46 papers shown

Title
Unveiling and Causalizing CoT: A Causal Pespective Jiarun Fu LiZhong Ding Hao Li P. Li Qiuning Wei Xu Chen LRM 132 0 0 25 Feb 2025
Scalable Out-of-distribution Robustness in the Presence of Unobserved Confounders Parjanya Prashant Seyedeh Baharan Khatami Bruno Ribeiro Babak Salimi 181 1 0 29 Nov 2024
Controlling for Unobserved Confounding with Large Language Model Classification of Patient Smoking Status Samuel Lee Zach Wood-Doughty CML 65 0 0 05 Nov 2024
Estimating Individual Dose-Response Curves under Unobserved Confounders from Observational Data Shutong Chen Yang Li CML 121 0 0 21 Oct 2024
Causal Inference with Latent Variables: Recent Advances and Future Prospectives Yaochen Zhu Yinhan He Jing Ma Mengxuan Hu Sheng Li Jundong Li CML 75 3 0 20 Jun 2024
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View Haoyue Dai Ignavier Ng Gongxu Luo Peter Spirtes P. Stojanov Kun Zhang CML 68 7 0 21 Mar 2024
Recovering Latent Confounders from High-dimensional Proxy Variables Nathan Mankovich Homer Durand Emiliano Díaz Gherardo Varando Gustau Camps-Valls 48 0 0 21 Mar 2024
Proximal Causal Inference With Text Data Jacob M. Chen Rohit Bhattacharya Katherine A. Keith 75 2 0 12 Jan 2024
Conditional Modeling Based Automatic Video Summarization Jia-Hong Huang Chao-Han Huck Yang Pin-Yu Chen Min-Hung Chen Marcel Worring VGen 90 5 0 20 Nov 2023
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs Jacqueline R. M. A. Maasch Weishen Pan Shantanu Gupta Volodymyr Kuleshov Kyra Gan Fei Wang 81 7 0 25 Oct 2023
Dissecting Causal Biases Ruta Binkyt.e Sami Zhioua Yassine Turki CML FaML 55 2 0 20 Oct 2023
Kernel Single Proxy Control for Deterministic Confounding Liyuan Xu Arthur Gretton CML 87 3 0 08 Aug 2023
Causal Video Summarizer for Video Exploration Jia-Hong Huang Chao-Han Huck Yang Pin-Yu Chen Andrew Brown Marcel Worring VGen 70 9 0 04 Jul 2023
Identifiable causal inference with noisy treatment and no side information Antti Pöllänen Pekka Marttinen CML 31 2 0 18 Jun 2023
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning Matthew Ashman Chao Ma Agrin Hilmkil Joel Jennings Cheng Zhang CML AI4CE 93 10 0 22 Mar 2023
Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders Defu Cao James Enouen Yujing Wang Xiangchen Song Chuizheng Meng Hao Niu Yan Liu CML 74 23 0 04 Mar 2023
Representation Disentaglement via Regularization by Causal Identification Juan Castorena OOD CML 137 0 0 28 Feb 2023
Estimating Treatment Effects in Continuous Time with Hidden Confounders Defu Cao James Enouen Yang Liu CML 82 2 0 19 Feb 2023
Adapting to Latent Subgroup Shifts via Concepts and Proxies Ibrahim Alabdulmohsin Nicole Chiou Alexander DÁmour Arthur Gretton Sanmi Koyejo Matt J. Kusner Stephen Pfohl Olawale Salaudeen Jessica Schrouff Katherine Tsai 130 11 0 21 Dec 2022
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error Yuqin Yang AmirEmad Ghassami M. Nafea Negar Kiyavash Kun Zhang I. Shpitser CML 45 8 0 08 Nov 2022
Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models Haoyue Dai Peter Spirtes Kun Zhang CML 41 10 0 20 Oct 2022
Innovations in Neural Data-to-text Generation: A Survey Mandar Sharma Ajay K. Gogineni Naren Ramakrishnan 101 10 0 25 Jul 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 122 59 0 31 Mar 2022
Deep Recurrent Modelling of Granger Causality with Latent Confounding Zexuan Yin P. Barucca CML BDL 53 13 0 23 Feb 2022
Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies Lu Cheng Ruocheng Guo Huan Liu CML 59 6 0 19 Dec 2021
Causal Effect Variational Autoencoder with Uniform Treatment Daniel Jiwoong Im Kyunghyun Cho N. Razavian OOD CML BDL 34 9 0 16 Nov 2021
Dependent Multi-Task Learning with Causal Intervention for Image Captioning Wenqing Chen Jidong Tian Caoyun Fan Hao He Yaohui Jin CML 123 6 0 18 May 2021
Causal Mediation Analysis with Hidden Confounders Lu Cheng Ruocheng Guo Huan Liu CML 91 16 0 21 Feb 2021
Generating Synthetic Text Data to Evaluate Causal Inference Methods Zach Wood-Doughty I. Shpitser Mark Dredze SyDa CML 68 11 0 10 Feb 2021
Causal Effects of Linguistic Properties Reid Pryzant Dallas Card Dan Jurafsky Victor Veitch Dhanya Sridhar CML 121 49 0 24 Oct 2020
From Optimizing Engagement to Measuring Value S. Milli Luca Belli Moritz Hardt 54 47 0 21 Aug 2020
Structural Causal Models Are (Solvable by) Credal Networks Marco Zaffalon Alessandro Antonucci Rafael Cabañas 53 23 0 02 Aug 2020
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders Andrew Bennett Nathan Kallus Lihong Li Ali Mousavi OffRL 84 44 0 27 Jul 2020
Estimating Granger Causality with Unobserved Confounders via Deep Latent-Variable Recurrent Neural Network Yuan Meng CML BDL 137 3 0 09 Sep 2019
Policy Evaluation with Latent Confounders via Optimal Balance Andrew Bennett Nathan Kallus CML 69 18 0 06 Aug 2019
Adapting Text Embeddings for Causal Inference Victor Veitch Dhanya Sridhar David M. Blei CML 61 21 0 29 May 2019
Semiparametric Methods for Exposure Misclassification in Propensity Score-Based Time-to-Event Data Analysis Yingrui Yang Molin Wang 18 0 0 19 Mar 2019
Using Embeddings to Correct for Unobserved Confounding in Networks Victor Veitch Yixin Wang David M. Blei CML 91 58 0 11 Feb 2019
Learning Models from Data with Measurement Error: Tackling Underreporting R. Adams Yuelong Ji Xiaobin Wang Suchi Saria 58 9 0 25 Jan 2019
Deconfounding Reinforcement Learning in Observational Settings Chaochao Lu Bernhard Schölkopf José Miguel Hernández-Lobato CML OOD 173 75 0 26 Dec 2018
Estimating Causal Effects With Partial Covariates For Clinical Interpretability S. Parbhoo Mario Wieser Volker Roth CML 21 0 0 26 Nov 2018
Estimation of Individual Treatment Effect in Latent Confounder Models via Adversarial Learning Changhee Lee Nicholas Mastronarde M. Schaar FedML CML 45 18 0 21 Nov 2018
An Upper Bound for Random Measurement Error in Causal Discovery Tineke Blom A. Klimovskaia Sara Magliacane Joris M. Mooij 61 11 0 18 Oct 2018
Challenges of Using Text Classifiers for Causal Inference Zach Wood-Doughty I. Shpitser Mark Dredze CML 66 73 0 01 Oct 2018
Cause-Effect Deep Information Bottleneck For Systematically Missing Covariates S. Parbhoo Mario Wieser Aleksander Wieczorek Volker Roth CML 85 5 0 06 Jul 2018
Causal Effect Inference with Deep Latent-Variable Models Christos Louizos Uri Shalit Joris Mooij David Sontag R. Zemel Max Welling CML BDL 242 750 0 24 May 2017