Causal Effect

Causal effect estimation aims to determine the impact of an intervention or treatment on an outcome, accounting for confounding factors that might obscure the true relationship. Current research focuses on improving estimation accuracy and robustness, particularly in complex settings with high-dimensional data, multiple treatments, and unobserved variables, employing techniques like double machine learning, graph neural networks, and Bayesian methods. These advancements are crucial for reliable causal inference across diverse fields, enabling more informed decision-making in areas such as healthcare, social sciences, and business, where understanding cause-and-effect relationships is paramount.

Papers

June 18, 2023

Identifiable causal inference with noisy treatment and no side information
Antti Pöllänen, Pekka Marttinen
Causal Inference Causal Effect Side Information Biased Causal Effect

June 16, 2023

Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions
Çağlar Hızlı, ST John, Anne Juuti, Tuure Saarinen, Kirsi Pietiläinen, Pekka Marttinen
Causal Effect Causal Model Point Process Causal Mediation Analysis Soft Intervention

June 15, 2023

Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding
Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan, Fred Morstatter
Causal Inference Causal Effect Prediction Interval Hidden Knowledge

June 10, 2023

Functional Causal Bayesian Optimization
Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa
Bayesian Optimization Causal Graph Causal Effect Causal Bayesian Optimization

June 8, 2023

June 1, 2023

May 27, 2023

Inferring Individual Direct Causal Effects Under Heterogeneous Peer Influence
Shishir Adhikari, Elena Zheleva
Causal Inference Causal Effect Peer Effect

May 26, 2023

May 17, 2023

A Survey on Causal Discovery: Theory and Practice
Alessio Zanga, Fabio Stella
Timely Survey Causal Inference Theoretical Understanding Causal Discovery Causal Graph Causal Effect Practice Mode Causal Pattern

May 16, 2023

Transfer Learning for Causal Effect Estimation
Song Wei, Hanyu Zhang, Ronald Moore, Rishikesan Kamaleswaran, Yao Xie
Transfer Learning Causal Effect Treatment Effect Causal Effect Estimation Causal Learning Downstream Decision Making

May 15, 2023

May 11, 2023

Integrating Nearest Neighbors with Neural Network Models for Treatment Effect Estimation
Niki Kiriakidou, Christos Diou
Deep Learning Causal Inference Causal Effect Neural Network Model Treatment Effect

April 21, 2023

A Common Misassumption in Online Experiments with Machine Learning Models
Olivier Jeunen
Machine Learning Model Causal Effect Causal Effect Estimation Randomized Controlled Trial Online Experiment

April 10, 2023

Linking a predictive model to causal effect estimation
Jiuyong Li, Lin Liu, Ziqi Xu, Ha Xuan Tran, Thuc Duy Le, Jixue Liu
Predictive Model Causal Effect Causal Effect Estimation

March 29, 2023

Using Connected Vehicle Trajectory Data to Evaluate the Effects of Speeding
Jorge Ugan, Mohamed Abdel-Aty, Zubayer Islam
Mixed Effect Causal Effect Speed Effect Vehicle Data Speed Map

March 24, 2023

Towards Learning and Explaining Indirect Causal Effects in Neural Networks
Abbavaram Gowtham Reddy, Saketh Bachu, Harsharaj Pathak, Benin L Godfrey, Vineeth N. Balasubramanian, Varshaneya V, Satya Narayanan Kar
Neural Network LeArning Abstract Causal Effect Structural Causal Model