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

April 24, 2023

Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion
Ziqi Xu, Debo Cheng, Jiuyong Li, Jixue Liu, Lin Liu, Kui Yu
Causal Inference Variational Autoencoder Causal Effect Estimation Unobserved Confounders Causal Strength Front Door Criterion

April 17, 2023

April 5, 2023

A step towards the applicability of algorithms based on invariant causal learning on observational data
Borja Guerrero Santillan
Practical Algorithm Causal Inference Causal Discovery Observational Data Causal Discovery Method Sample STEP Applicability Study Optimal Prediction Invariant Causal Feature Invariant Causal

March 24, 2023

March 20, 2023

Approaching an unknown communication system by latent space exploration and causal inference
Gašper Beguš, Andrej Leban, Shane Gero
Latent Space Causal Inference Meaningful Representation Causal Disentanglement Unsupervised Generative Animal Communication

March 7, 2023

Learning When to Treat Business Processes: Prescriptive Process Monitoring with Causal Inference and Reinforcement Learning
Zahra Dasht Bozorgi, Marlon Dumas, Marcello La Rosa, Artem Polyvyanyy, Mahmoud Shoush, Irene Teinemaa
Reinforcement Learning LeArning Abstract Causal Inference Decision Making Business Process Learning Mechanism Continuous Improvement Prescriptive Process Monitoring

March 6, 2023

Environment Invariant Linear Least Squares
Jianqing Fan, Cong Fang, Yihong Gu, Tong Zhang
Causal Inference Least Square Global Endogenous Variate Conditional Invariance

March 3, 2023

PAGE: A Position-Aware Graph-Based Model for Emotion Cause Entailment in Conversation
Xiaojie Gu, Renze Lou, Lin Sun, Shangxin Li
Causal Inference Target Emotion Causal Relation Potential Conversation Outcome Web Page Causal Emotion Entailment Position Aware Graph

March 2, 2023

Hyperparameter Tuning and Model Evaluation in Causal Effect Estimation
Damian Machlanski, Spyridon Samothrakis, Paul Clarke
Causal Inference Causal Discovery Causal Effect Hyperparameter Tuning Causal Effect Estimation Model Evaluation

February 23, 2023

Variable Importance Matching for Causal Inference
Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
Causal Inference Treatment Effect Multiple Outcome Variable Importance Observational Causal Model Matching

February 22, 2023

Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference
Sahara Ali, Omar Faruque, Yiyi Huang, Md. Osman Gani, Aneesh Subramanian, Nicole-Jienne Shchlegel, Jianwu Wang
Deep Learning Causal Inference Time Varying Sea Ice

February 20, 2023

Mental Health Coping Stories on Social Media: A Causal-Inference Study of Papageno Effect
Yunhao Yuan, Koustuv Saha, Barbara Keller, Erkki Tapio Isometsä, Talayeh Aledavood
Social Medium Causal Inference Mental Health Social Medium Data Lombard Effect Mental Well Cognitive Effect

February 19, 2023

Estimating Treatment Effects in Continuous Time with Hidden Confounders
Defu Cao, James Enouen, Yan Liu
Causal Inference Differential Equation Treatment Effect Continuous Time Text Based Confounders

February 10, 2023

Causal Inference out of Control: Estimating the Steerability of Consumption
Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner
External Control Causal Inference Causal Effect Consumption Data Steerable Robot Causal Identifiability

February 6, 2023

Causal Estimation of Exposure Shifts with Neural Networks
Mauricio Tec, Kevin Josey, Oladimeji Mudele, Francesca Dominici
Neural Network Causal Inference Causal Effect Causal Effect Estimation Air Pollution Frequency Response Exposure Data Robust Causal

February 3, 2023

Causal Inference Based Single-branch Ensemble Trees For Uplift Modeling
Fanglan Zheng, Menghan Wang, Kun Li, Jiang Tian, Xiaojia Xiang
Causal Inference Uplift Modeling Tree Based Ensemble Causal Forest Inference Rule Predictive Probability

February 2, 2023

Causal Effect Estimation: Recent Advances, Challenges, and Opportunities
Zhixuan Chu, Jianmin Huang, Ruopeng Li, Wei Chu, Sheng Li
Technical Challenge Causal Inference Emerging Opportunity Recent Advance Treatment Effect Causal Effect Estimation

February 1, 2023

How to select predictive models for causal inference?
Matthieu Doutreligne, Gaël Varoquaux
Causal Inference Feature Selection Predictive Model Causal Effect Causal Inference Task