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On Measurement Bias in Causal Inference

On Measurement Bias in Causal Inference

15 March 2012
Judea Pearl
    CML
ArXiv (abs)PDFHTML

Papers citing "On Measurement Bias in Causal Inference"

46 / 46 papers shown
Title
Unveiling and Causalizing CoT: A Causal Pespective
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
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
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
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
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
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
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
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
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
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
Dissecting Causal Biases
Ruta Binkyt.e
Sami Zhioua
Yassine Turki
CMLFaML
55
2
0
20 Oct 2023
Kernel Single Proxy Control for Deterministic Confounding
Kernel Single Proxy Control for Deterministic Confounding
Liyuan Xu
Arthur Gretton
CML
87
3
0
08 Aug 2023
Causal Video Summarizer for Video Exploration
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
Identifiable causal inference with noisy treatment and no side information
Antti Pöllänen
Pekka Marttinen
CML
33
2
0
18 Jun 2023
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG
  Learning
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning
Matthew Ashman
Chao Ma
Agrin Hilmkil
Joel Jennings
Cheng Zhang
CMLAI4CE
93
10
0
22 Mar 2023
Estimating Treatment Effects from Irregular Time Series Observations
  with Hidden Confounders
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
Representation Disentaglement via Regularization by Causal Identification
Juan Castorena
OODCML
137
0
0
28 Feb 2023
Estimating Treatment Effects in Continuous Time with Hidden Confounders
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
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
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
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
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
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning
Chuizheng Meng
Sungyong Seo
Defu Cao
Sam Griesemer
Yan Liu
PINNAI4CE
122
59
0
31 Mar 2022
Deep Recurrent Modelling of Granger Causality with Latent Confounding
Deep Recurrent Modelling of Granger Causality with Latent Confounding
Zexuan Yin
P. Barucca
CMLBDL
53
13
0
23 Feb 2022
Estimating Causal Effects of Multi-Aspect Online Reviews with
  Multi-Modal Proxies
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
Causal Effect Variational Autoencoder with Uniform Treatment
Daniel Jiwoong Im
Kyunghyun Cho
N. Razavian
OODCMLBDL
34
9
0
16 Nov 2021
Dependent Multi-Task Learning with Causal Intervention for Image
  Captioning
Dependent Multi-Task Learning with Causal Intervention for Image Captioning
Wenqing Chen
Jidong Tian
Caoyun Fan
Hao He
Yaohui Jin
CML
130
6
0
18 May 2021
Causal Mediation Analysis with Hidden Confounders
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
Generating Synthetic Text Data to Evaluate Causal Inference Methods
Zach Wood-Doughty
I. Shpitser
Mark Dredze
SyDaCML
68
11
0
10 Feb 2021
Causal Effects of Linguistic Properties
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
From Optimizing Engagement to Measuring Value
S. Milli
Luca Belli
Moritz Hardt
60
47
0
21 Aug 2020
Structural Causal Models Are (Solvable by) Credal Networks
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
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
Estimating Granger Causality with Unobserved Confounders via Deep Latent-Variable Recurrent Neural Network
Yuan Meng
CMLBDL
144
3
0
09 Sep 2019
Policy Evaluation with Latent Confounders via Optimal Balance
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
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
27
0
0
19 Mar 2019
Using Embeddings to Correct for Unobserved Confounding in Networks
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
Learning Models from Data with Measurement Error: Tackling Underreporting
R. Adams
Yuelong Ji
Xiaobin Wang
Suchi Saria
63
9
0
25 Jan 2019
Deconfounding Reinforcement Learning in Observational Settings
Deconfounding Reinforcement Learning in Observational Settings
Chaochao Lu
Bernhard Schölkopf
José Miguel Hernández-Lobato
CMLOOD
173
75
0
26 Dec 2018
Estimating Causal Effects With Partial Covariates For Clinical
  Interpretability
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
Estimation of Individual Treatment Effect in Latent Confounder Models via Adversarial Learning
Changhee Lee
Nicholas Mastronarde
M. Schaar
FedMLCML
49
18
0
21 Nov 2018
An Upper Bound for Random Measurement Error in Causal Discovery
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
Challenges of Using Text Classifiers for Causal Inference
Zach Wood-Doughty
I. Shpitser
Mark Dredze
CML
70
73
0
01 Oct 2018
Cause-Effect Deep Information Bottleneck For Systematically Missing
  Covariates
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
Causal Effect Inference with Deep Latent-Variable Models
Christos Louizos
Uri Shalit
Joris Mooij
David Sontag
R. Zemel
Max Welling
CMLBDL
242
750
0
24 May 2017
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