Causal Inference

January 12, 2024

Modeling Latent Selection with Structural Causal Models
Leihao Chen, Onno Zoeter, Joris M. Mooij
Causal Inference Structural Causal Model Latent Evolution
Deep Learning With DAGs
Sourabh Balgi, Adel Daoud, Jose M. Peña, Geoffrey T. Wodtke, Jesse Zhou
Deep Learning Causal Inference Causal Effect Causal Relationship Directed Acyclic Graph Parametric Causal Graphical Normalizing Flow
Proximal Causal Inference With Text Data
Jacob M. Chen, Rohit Bhattacharya, Katherine A. Keith
Causal Inference Text Data Proximal Causal Causal Text Mining

January 5, 2024

Neural Causal Abstractions
Kevin Xia, Elias Bareinboim
Causal Inference Causal Abstraction Causal Inference Task Neural Causal Model

December 24, 2023

The Challenge of Using LLMs to Simulate Human Behavior: A Causal Inference Perspective
George Gui, Olivier Toubia
Large Language Model Causal Inference Challenge Task Human Behavior Conditional Average Treatment Effect Global Endogenous Variate LLM Simulation

December 23, 2023

December 22, 2023

Zero-shot Causal Graph Extrapolation from Text via LLMs
Alessandro Antonucci, Gregorio Piqué, Marco Zaffalon
Large Language Model Text Modality Causal Inference Causal Graph Causal Relation Causal View Ground Truth Causal Zero Shot Causal

December 14, 2023

Casual Social Media Use among the Youth: Effects on Online and Offline Political Participation
Mehdi Barati
Social Medium Mixed Effect Causal Inference Online Service

December 13, 2023

Double Machine Learning for Static Panel Models with Fixed Effects
Paul S. Clarke, Annalivia Polselli
Causal Inference Double Machine Learning Panel Data Fixed Effect

December 12, 2023

Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders
Debo Cheng, Ziqi Xu, Jiuyong Li, Lin Liu, Jixue Liu, Wentao Gao, Thuc Duy Le
Causal Inference Time Varying Instrumental Variable Longitudinal Data Factor Model

December 10, 2023

Learning the Causal Structure of Networked Dynamical Systems under Latent Nodes and Structured Noise
Augusto Santos, Diogo Rente, Rui Seabra, José M. F. Moura
LeArning Abstract Causal Inference Dynamical System Latent Representation Causal Structure Partial Observability Correlated Noise Causal Network

December 8, 2023

Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal Inference
Debo Cheng, Yang Xie, Ziqi Xu, Jiuyong Li, Lin Liu, Jixue Liu, Yinghao Zhang, Zaiwen Feng
Causal Inference Latent Confounders Bias Related Issue Disentangled Latent

December 7, 2023

December 3, 2023

Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits
Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish, Jean-Francois Ton
Causal Inference Contextual Bandit Policy Evaluation Inverse Propensity Inverse Probability Weighting

December 1, 2023

SpaCE: The Spatial Confounding Environment
Mauricio Tec, Ana Trisovic, Michelle Audirac, Sophie Woodward, Jie Kate Hu, Naeem Khoshnevis, Francesca Dominici
Causal Inference Causal Discovery Deep Space Spatial Dependence

November 30, 2023

Geometry-Aware Normalizing Wasserstein Flows for Optimal Causal Inference
Kaiwen Hou
Causal Inference Normalizing Flow Wasserstein Gradient Wasserstein Gradient Flow

November 29, 2023

Entropy and the Kullback-Leibler Divergence for Bayesian Networks: Computational Complexity and Efficient Implementation
Marco Scutari
Causal Inference Bayesian Network Kullback Leibler Divergence Computational Complexity Distributional Assumption Stable Entropy Graphical Structure Gaussian Bayesian Network

November 28, 2023

FedECA: A Federated External Control Arm Method for Causal Inference with Time-To-Event Data in Distributed Settings
Jean Ogier du Terrail, Quentin Klopfenstein, Honghao Li, Imke Mayer, Nicolas Loiseau, Mohammad Hallal, Michael Debouver, Thibault Camalon, Thibault Fouqueray, Jorge Arellano Castro, Zahia Yanes, Laetitia Dahan, Julien Taïeb, Pierre Laurent-Puig, Jean-Baptiste Bachet, Shulin Zhao, Remy Nicolle, Jérome Cros, Daniel Gonzalez, Robert Carreras-Torres, Adelaida Garcia Velasco, Kawther Abdilleh, Sudheer Doss, Félix Balazard, Mathieu Andreux
Causal Inference Data Sharing Privacy Enhancing Technology Time to Event Data

Papers

Modeling Latent Selection with Structural Causal Models

Deep Learning With DAGs

Proximal Causal Inference With Text Data

Neural Causal Abstractions

The Challenge of Using LLMs to Simulate Human Behavior: A Causal Inference Perspective

An Explainable AI Approach to Large Language Model Assisted Causal Model Auditing and Development

Causal Forecasting for Pricing

Zero-shot Causal Graph Extrapolation from Text via LLMs

Casual Social Media Use among the Youth: Effects on Online and Offline Political Participation

Double Machine Learning for Static Panel Models with Fixed Effects

Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders

Learning the Causal Structure of Networked Dynamical Systems under Latent Nodes and Structured Noise

Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal Inference

CLadder: Assessing Causal Reasoning in Language Models

Causality and Explainability for Trustworthy Integrated Pest Management

Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits

SpaCE: The Spatial Confounding Environment

Geometry-Aware Normalizing Wasserstein Flows for Optimal Causal Inference

Entropy and the Kullback-Leibler Divergence for Bayesian Networks: Computational Complexity and Efficient Implementation

FedECA: A Federated External Control Arm Method for Causal Inference with Time-To-Event Data in Distributed Settings