Causal Effect

Causal effect estimation aims to determine the impact of an intervention or treatment on an outcome, accounting for confounding factors that might obscure the true relationship. Current research focuses on improving estimation accuracy and robustness, particularly in complex settings with high-dimensional data, multiple treatments, and unobserved variables, employing techniques like double machine learning, graph neural networks, and Bayesian methods. These advancements are crucial for reliable causal inference across diverse fields, enabling more informed decision-making in areas such as healthcare, social sciences, and business, where understanding cause-and-effect relationships is paramount.

Papers

December 24, 2024

PCM Selector: Penalized Covariate-Mediator Selection Operator for Evaluating Linear Causal Effects
Hisayoshi Nanmo, Manabu Kuroki
Causal Effect Relevant Covariates Structural Equation Causal Mediation Analysis Network Selection

December 13, 2024

Class flipping for uplift modeling and Heterogeneous Treatment Effect estimation on imbalanced RCT data
Krzysztof Rudaś, Szymon Jaroszewicz
Estimation Task Causal Effect Heterogeneous Treatment Effect Uplift Modeling Randomized Experiment Causal Interpretation

December 5, 2024

December 4, 2024

Online Experimental Design With Estimation-Regret Trade-off Under Network Interference
Zhiheng Zhang, Zichen Wang
Scientific Inference Causal Effect Causal Direction Online Experiment Network Interference

December 3, 2024

November 28, 2024

November 26, 2024

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data
Debo Cheng (1), Ziqi Xu (2), Jiuyong Li (1), Lin Liu (1), Thuc duy Le (1), Xudong Guo (1), Shichao Zhang (3) ((1) University of South Australia (2) RMIT University (3) Guangxi Normal University)
Causal Effect Time Series Data Time Varying Causal Effect Estimation Instrumental Variable

November 25, 2024

Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables
Zheng Li, Feng Xie, Yan Zeng, Zhi Geng
Estimation Task Latent Variable Causal Effect Causal Relationship Variable Selection Local Learning Parametric Causal

November 18, 2024

Causal Effect of Group Diversity on Redundancy and Coverage in Peer-Reviewing
Navita Goyal, Ivan Stelmakh, Nihar Shah, Hal Daumé III
Causal Effect Diversity Awareness Information Redundancy Peer Review Higher Coverage Rate Human Reviewer Co Authorship Network Diverse Evaluation

November 17, 2024

Program Evaluation with Remotely Sensed Outcomes
Ashesh Rambachan, Rahul Singh, Davide Viviano
Remote Sensing Causal Effect Treatment Effect Recent Research Treatment Variable

November 15, 2024

Graph-based Complexity for Causal Effect by Empirical Plug-in
Rina Dechter, Annie Raichev, Alexander Ihler, Jin Tian
Causal Graph Causal Effect Graphical Model Causal Query Generic Plugin

November 10, 2024

CRTRE: Causal Rule Generation with Target Trial Emulation Framework
Junda Wang, Weijian Li, Han Wang, Hanjia Lyu, Caroline P. Thirukumaran, Addisu Mesfin, Hong Yu, Jiebo Luo
Causal Inference Causal Effect Model Interpretability Causal Event Randomized Controlled Trial

November 5, 2024

Controlling for Unobserved Confounding with Large Language Model Classification of Patient Smoking Status
Samuel Lee, Zach Wood-Doughty
Large Language Model Classification Code Causal Inference Causal Effect Unobserved Confounders Causal Interpretation Unmeasured Confounding Unobservable State

November 2, 2024

Marginal Causal Flows for Validation and Inference
Daniel de Vassimon Manela, Laura Battaglia, Robin J. Evans
Scientific Inference Causal Discovery Causal Effect External Validation Causal View Unmeasured Confounding Graphical Normalizing Flow

October 31, 2024

Average Controlled and Average Natural Micro Direct Effects in Summary Causal Graphs
Simon Ferreira, Charles K. Assaad
Causal Inference Causal Graph Causal Effect Causal System Average Performance Summary Causal Graph

October 29, 2024

Bayesian Counterfactual Prediction Models for HIV Care Retention with Incomplete Outcome and Covariate Information
Arman Oganisian, Joseph Hogan, Edwin Sang, Allison DeLong, Ben Mosong, Hamish Fraser, Ann Mwangi
Causal Inference Causal Effect Relevant Covariates Multiple Outcome Counterfactual Prediction Confounding Bias Optimal Scheduling

October 28, 2024

Deep Learning Methods for the Noniterative Conditional Expectation G-Formula for Causal Inference from Complex Observational Data
Sophia M Rein, Jing Li, Miguel Hernan, Andrew Beam
Deep Learning Causal Inference Causal Effect Generalized Linear Model Mathematical Formula Classical Data Conditional Expectation Deep Neural Network Estimator

Causal Effect

Papers

PCM Selector: Penalized Covariate-Mediator Selection Operator for Evaluating Linear Causal Effects

Class flipping for uplift modeling and Heterogeneous Treatment Effect estimation on imbalanced RCT data

Disentangled Representation Learning for Causal Inference with Instruments

Deep Causal Inference for Point-referenced Spatial Data with Continuous Treatments

Online Experimental Design With Estimation-Regret Trade-off Under Network Interference

Constrained Identifiability of Causal Effects

Nature versus nurture in galaxy formation: the effect of environment on star formation with causal machine learning

Contrastive representations of high-dimensional, structured treatments

I See, Therefore I Do: Estimating Causal Effects for Image Treatments

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data

Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables

Causal Effect of Group Diversity on Redundancy and Coverage in Peer-Reviewing

Program Evaluation with Remotely Sensed Outcomes

Graph-based Complexity for Causal Effect by Empirical Plug-in

CRTRE: Causal Rule Generation with Target Trial Emulation Framework

Controlling for Unobserved Confounding with Large Language Model Classification of Patient Smoking Status

Marginal Causal Flows for Validation and Inference

Average Controlled and Average Natural Micro Direct Effects in Summary Causal Graphs

Bayesian Counterfactual Prediction Models for HIV Care Retention with Incomplete Outcome and Covariate Information

Deep Learning Methods for the Noniterative Conditional Expectation G-Formula for Causal Inference from Complex Observational Data