Causal Parameter

Causal parameter estimation aims to quantify the effect of one variable on another, accounting for confounding factors. Current research focuses on developing efficient algorithms for identifying and estimating these parameters within various model frameworks, including linear structural causal models and those incorporating latent variables, often leveraging techniques like instrumental variables and higher-order cumulants. A significant challenge lies in handling computational complexity and ensuring the robustness of estimates, particularly in the presence of unobserved confounders or high-dimensional data. These advancements have broad implications for diverse fields, enabling more reliable causal inference in areas such as medicine, social sciences, and policy evaluation.

Papers

July 17, 2024

On the Complexity of Identification in Linear Structural Causal Models
Julian Dörfler, Benito van der Zander, Markus Bläser, Maciej Liskiewicz
Person Identification Complexity Matter Structural Causal Model Covariance Matrix Novel Identifiability Test Parameter Identification Causal Parameter

June 4, 2024

Orthogonal Causal Calibration
Justin Whitehouse, Christopher Jung, Vasilis Syrgkanis, Bryan Wilder, Zhiwei Steven Wu
Causal Effect Estimation Nuisance Parameter Causal Parameter Higher Order Loss

December 19, 2023

Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants
Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang
Causal Discovery Person Identification Latent Variable Causal Structure Causal Direction Order Cumulants Causal Parameter

November 23, 2023

Identification for Tree-shaped Structural Causal Models in Polynomial Time
Aaryan Gupta, Markus Bläser
Person Identification Causal Effect Structural Causal Model Polynomial Time Causal Parameter

October 31, 2023

Text-Transport: Toward Learning Causal Effects of Natural Language
Victoria Lin, Louis-Philippe Morency, Eli Ben-Michael
Natural Language Causal Inference Causal Effect Real Text Word Causal Parameter

March 24, 2023

Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions
Abhineet Agarwal, Anish Agarwal, Suhas Vijaykumar
Causal Inference New Combination Factorial Design Causal Parameter

June 3, 2022

Debiased Machine Learning without Sample-Splitting for Stable Estimators
Qizhao Chen, Vasilis Syrgkanis, Morgane Austern
Estimation Task Auxiliary Objective Causal Parameter Ensemble Bagging

March 3, 2022

Identification in Tree-shaped Linear Structural Causal Models
Benito van der Zander, Marcel Wienöbst, Markus Bläser, Maciej Liśkiewicz
Person Identification Causal Effect Instrumental Variable Structural Equation Structural Characterization Causal Parameter

December 28, 2021

Nested Nonparametric Instrumental Variable Regression: Long Term, Mediated, and Time Varying Treatment Effects
Isaac Meza, Rahul Singh
Long Term Ill Posed Inverse Problem Panel Data Causal Parameter Nonparametric Instrumental Variable Time Varying Treatment

December 26, 2021

Long Story Short: Omitted Variable Bias in Causal Machine Learning
Victor Chernozhukov, Carlos Cinelli, Whitney Newey, Amit Sharma, Vasilis Syrgkanis
Covariate Shift Causal Machine Learning Causal Machine Systematic Bias Average Causal Effect Long Story Causal Parameter