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

January 28, 2022

Unifying Pairwise Interactions in Complex Dynamics
Oliver M. Cliff, Annie G. Bryant, Joseph T. Lizier, Naotsugu Tsuchiya, Ben D. Fulcher
Causal Inference Complex Dynamic Pairwise Interaction

January 26, 2022

Promises and Challenges of Causality for Ethical Machine Learning
Aida Rahmattalabi, Alice Xiang
Technical Challenge Causal Inference Causal Pattern Promise Responsible Machine Learning Causal Fairness

January 25, 2022

Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery
Aida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud, Eric Rice
Application Proficiency Causal Inference Resource Allocation Mixed Integer Fairness Constraint Observational Data Interpretable Policy

January 15, 2022

Automated causal inference in application to randomized controlled clinical trials
Jiqing Wu, Nanda Horeweg, Marco de Bruyn, Remi A. Nout, Ina M. Jürgenliemk-Schulz, Ludy C. H. W. Lutgens, Jan J. Jobsen, Elzbieta M. van der Steen-Banasik, Hans W. Nijman, Vincent T. H. B. M. Smit, Tjalling Bosse, Carien L. Creutzberg, Viktor H. Koelzer
Application Proficiency Causal Inference Clinical Trial Causal Variable Causal Interpretation

January 11, 2022

Ancestral Instrument Method for Causal Inference without Complete Knowledge
Debo Cheng, Jiuyong Li, Lin Liu, Jiji Zhang, Thuc duy Le, Jixue Liu
Causal Inference Causal Relationship Causal Effect Estimation Instrumental Variable Ancestral Sampling

December 27, 2021

Deep Treatment-Adaptive Network for Causal Inference
Qian Li, Zhichao Wang, Shaowu Liu, Gang Li, Guandong Xu
Causal Inference Treatment Effect Relevant Covariates Treatment Selection Bias Balanced Representation

December 22, 2021

Causal Inference Despite Limited Global Confounding via Mixture Models
Spencer L. Gordon, Bijan Mazaheri, Yuval Rabani, Leonard J. Schulman
Causal Inference Causal Relationship Bayesian Network Mixture Model Causal Relation Non Confounding Covariates

December 21, 2021

Doubly-Valid/Doubly-Sharp Sensitivity Analysis for Causal Inference with Unmeasured Confounding
Jacob Dorn, Kevin Guo, Nathan Kallus
Causal Inference Robust Optimization Unobserved Confounders Sensitivity Analysis Semi Parametric Partial Identifiability Unmeasured Confounding

December 19, 2021

December 10, 2021

Causal Knowledge Guided Societal Event Forecasting
Songgaojun Deng, Huzefa Rangwala, Yue Ning
Causal Inference Causal Effect Estimation Event Forecasting

December 9, 2021

Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving
Lei Ding, Dengdeng Yu, Jinhan Xie, Wenxing Guo, Shenggang Hu, Meichen Liu, Linglong Kong, Hongsheng Dai, Yanchun Bao, Bei Jiang
Causal Inference Word Embeddings Gender Bias Semantic Preservation Gender Classification Bias

December 1, 2021

AI Assurance using Causal Inference: Application to Public Policy
Andrei Svetovidov, Abdul Rahman, Feras A. Batarseh
Application Proficiency Causal Inference AI System Cause Effect Public Policy

November 27, 2021

A Two-Stage Feature Selection Approach for Robust Evaluation of Treatment Effects in High-Dimensional Observational Data
Md Saiful Islam, Sahil Shikalgar, Md. Noor-E-Alam
High Dimensional Causal Inference Feature Selection Treatment Effect Robust Evaluation Randomized Controlled Trial Elastic Net Robust Causal

November 11, 2021

Variational Auto-Encoder Architectures that Excel at Causal Inference
Negar Hassanpour, Russell Greiner
Causal Inference Causal Effect Generative Approach Variational Auto Observational Data

November 9, 2021

Generalized Kernel Ridge Regression for Causal Inference with Missing-at-Random Sample Selection
Rahul Singh
Causal Inference Treatment Effect Relevant Covariates Kernel Ridge Regression Semi Parametric Dose Response

November 7, 2021

Positivity Validation Detection and Explainability via Zero Fraction Multi-Hypothesis Testing and Asymmetrically Pruned Decision Trees
Guy Wolf, Gil Shabat, Hanan Shteingart
High Explainability Causal Inference Causal Analysis Multiple Hypothesis Testing Negative Pseudo Label Sparse Decision Tree

November 4, 2021

Causal inference with imperfect instrumental variables
Nikolai Miklin, Mariami Gachechiladze, George Moreno, Rafael Chaves
Causal Inference Instrumental Variable Causal Assumption Statistical Dependency Societal Inequality

September 24, 2021

Optimization-based Causal Estimation from Heterogenous Environments
Mingzhang Yin, Yixin Wang, David M. Blei
Causal Inference Causal Model Causal Relationship Causal Effect Estimation Causal Explanation Heterogeneity Environment