Causal Inference

Causal inference aims to determine cause-and-effect relationships from data, going beyond mere correlations to understand how interventions impact outcomes. Current research heavily focuses on addressing challenges like confounding (the influence of unobserved variables), particularly in high-dimensional data and complex treatments (e.g., text, sequences of actions), employing methods such as structural causal models, Bayesian Additive Regression Trees (BART), and various neural network architectures including Graph Neural Networks (GNNs). These advancements are crucial for improving the reliability of causal conclusions across diverse fields, from medicine and economics to personalized interventions and policy-making.

Papers

June 4, 2022

Discovering Ancestral Instrumental Variables for Causal Inference from Observational Data
Debo Cheng, Jiuyong Li, Lin Liu, Kui Yu, Thuc Duy Lee, Jixue Liu
Causal Inference Causal Effect Observational Data Instrumental Variable

June 2, 2022

May 30, 2022

Causal Explanations for Sequential Decision Making Under Uncertainty
Samer B. Nashed, Saaduddin Mahmud, Claudia V. Goldman, Shlomo Zilberstein
Markov Decision Process Causal Inference High Uncertainty Anticipation Structural Causal Model Sequential Decision Making Causal Explanation

May 29, 2022

Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects
Naoufal Acharki, Ramiro Lugo, Antoine Bertoncello, Josselin Garnier
Causal Inference Consistent Comparison Conditional Average Treatment Effect Meta Learner Heterogeneous Effect Valued Treatment

May 27, 2022

Detecting hidden confounding in observational data using multiple environments
Rickard K. A. Karlsson, Jesse H. Krijthe
Causal Inference Observational Data Unobserved Confounders Causal Variable Confounding Bias

May 26, 2022

Leveraging Causal Inference for Explainable Automatic Program Repair
Jianzong Wang, Shijing Si, Zhitao Zhu, Xiaoyang Qu, Zhenhou Hong, Jing Xiao
Causal Inference Causal Graph Program Repair

May 25, 2022

Identifying Patient-Specific Root Causes with the Heteroscedastic Noise Model
Eric V. Strobl, Thomas A. Lasko
Causal Inference Root Cause Heteroscedastic Noise

May 23, 2022

May 21, 2022

Neuroevolutionary Feature Representations for Causal Inference
Michael C. Burkhart, Gabriel Ruiz
Causal Inference Estimation Task Feature Representation Heterogeneous Treatment Effect Conditional Average Treatment Effect

May 20, 2022

What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment
Nathan Kallus
Causal Inference High Quality Counterfactuals Relevant Covariates Potential Harm Accurate Treatment Sharp Bound Robust Inference Robust Bayesian

May 19, 2022

Causal Inference from Small High-dimensional Datasets
Raquel Aoki, Martin Ester
High Dimensional Causal Inference Neural Estimator

May 6, 2022

DagSim: Combining DAG-based model structure with unconstrained data types and relations for flexible, transparent, and modularized data simulation
Ghadi S. Al Hajj, Johan Pensar, Geir Kjetil Sandve
Causal Inference Simulation Framework Simulated Data Inter Relation DAG Learning Simulation Model

May 1, 2022

Conceptualizing Treatment Leakage in Text-based Causal Inference
Adel Daoud, Connor T. Jerzak, Richard Johansson
Causal Inference Text Based Confounders Average Treatment Effect Causal Text Mining

April 21, 2022

A unified theory of information transfer and causal relation
Yang Tian, Hedong Hou, Yaoyuan Wang, Ziyang Zhang, Pei Sun
Causal Inference Causal Relationship Unified Model Information Transfer Causality Analysis Transfer Entropy Information Exchange

April 17, 2022

Causal Intervention for Subject-Deconfounded Facial Action Unit Recognition
Yingjie Chen, Diqi Chen, Tao Wang, Yizhou Wang, Yun Liang
Causal Inference Causal Intervention Causal Intervention Module Action Unit

April 14, 2022

Causal Disentanglement with Network Information for Debiased Recommendations
Paras Sheth, Ruocheng Guo, Lu Cheng, Huan Liu, K. Selçuk Candan
Recommender System Causal Inference Recommendation Model User Item Causal Disentanglement Debiased Recommendation Network Data

April 11, 2022

Causal Discovery and Causal Learning for Fire Resistance Evaluation: Incorporating Domain Knowledge
M. Z. Naser, Aybike Ozyuksel Ciftcioglu
Causal Inference Causal Discovery Domain Knowledge Causal Structure Causal Learning Causal Discovery Algorithm

April 4, 2022

Causality, Causal Discovery, and Causal Inference in Structural Engineering
M. Z. Naser
Causal Inference Causal Discovery Causal Model Causal Pattern Causal Approach Structural Engineering Causal Concept