Causal Inference Task

Causal inference tasks aim to determine cause-and-effect relationships from observational data, a crucial challenge across diverse scientific fields. Current research focuses on improving the accuracy and efficiency of causal effect estimation, particularly using deep neural networks in multi-stage learning frameworks and exploring representation learning techniques to optimize weighting methods. These advancements are significant for various applications, including policy evaluation, personalized medicine, and improving the reliability of scientific discoveries derived from observational studies, particularly in high-dimensional settings where traditional methods struggle. Furthermore, the field is actively investigating the capabilities and limitations of large language models in performing causal inference tasks, highlighting the need for robust benchmarks and careful consideration of potential biases.

Papers

October 15, 2024

Do LLMs Have the Generalization Ability in Conducting Causal Inference?
Chen Wang, Dongming Zhao, Bo Wang, Ruifang He, Yuexian Hou
Medical LLM Causal Inference Causal Inference Task

September 24, 2024

Towards Representation Learning for Weighting Problems in Design-Based Causal Inference
Oscar Clivio, Avi Feller, Chris Holmes
Representation Learning Causal Inference Causal Effect Causal Inference Task Dynamic Weight Optimal Weight

September 22, 2024

Testing Causal Models with Hidden Variables in Polynomial Delay via Conditional Independencies
Hyunchai Jeong, Adiba Ejaz, Jin Tian, Elias Bareinboim
Causal Graph Causal Model Conditional Independence Causal Inference Task

September 15, 2024

Causal Inference with Large Language Model: A Survey
Jing Ma
Large Language Model Timely Survey Causal Inference Causal Relation Causal Inference Task

July 11, 2024

Causal inference through multi-stage learning and doubly robust deep neural networks
Yuqian Zhang, Jelena Bradic
Deep Neural Network Causal Inference Multi Stage Robust Deep Conditional Average Treatment Effect Causal Inference Task Dynamic Treatment Effect

June 18, 2024

LLMs Are Prone to Fallacies in Causal Inference
Nitish Joshi, Abulhair Saparov, Yixin Wang, He He
Medical LLM Causal Inference Causal Relation Causal View Causal Inference Task Explicitly Mentioned Causal Fact

June 12, 2024

Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark Framework
Ruibo Tu, Zineb Senane, Lele Cao, Cheng Zhang, Hedvig Kjellström, Gustav Eje Henter
Causal Discovery Causal Pattern Tabular Data Synthesis Causal Inference Task

May 27, 2024

Smoke and Mirrors in Causal Downstream Tasks
Riccardo Cadei, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello
Causal Inference Causal Model Causal Effect Estimation Etruscan Mirror Causal Query Causal Inference Task

May 2, 2024

A deep causal inference model for fully-interpretable travel behaviour analysis
Kimia Kamal, Bilal Farooq
Causal Inference Travel Mode Causal Inference Task Travel Behavior Deep Causal

January 5, 2024

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

June 27, 2023

Predictive Coding beyond Correlations
Tommaso Salvatori, Luca Pinchetti, Amine M'Charrak, Beren Millidge, Thomas Lukasiewicz
Causal Graph Predictive Coding Total Correlation Plausible Learning Inference Strategy Causal Inference Task

June 9, 2023

Can Large Language Models Infer Causation from Correlation?
Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona Diab, Bernhard Schölkopf
Large Language Model Total Correlation Causal Inference Task Causal News Corpus

April 18, 2023

METAM: Goal-Oriented Data Discovery
Sainyam Galhotra, Yue Gong, Raul Castro Fernandez
Causal Inference Task Efficient Augmentation Goal Discovery

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

October 1, 2022

Transfer Learning for Individual Treatment Effect Estimation
Ahmed Aloui, Juncheng Dong, Cat P. Le, Vahid Tarokh
Transfer Learning Causal Knowledge Individual Treatment Effect Causal Inference Task Treatment Effect Estimation

August 15, 2022

Anticipating Performativity by Predicting from Predictions
Celestine Mendler-Dünner, Frances Ding, Yixin Wang
Human Prediction Causal Effect Causal Relationship Causal Inference Task Performative Power Causal Identifiability

June 13, 2022

Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention Recognition
Mingjie Li, Zeyan Li, Kanglin Yin, Xiaohui Nie, Wenchi Zhang, Kaixin Sui, Dan Pei
Causal Inference Root Cause Causal Event Causal Inference Task Causal Bayesian Network

November 19, 2021

A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling
Eustache Diemert, Artem Betlei, Christophe Renaudin, Massih-Reza Amini, Théophane Gregoir, Thibaud Rahier
Causal Effect Large Scale Benchmark Individual Treatment Effect Uplift Modeling Treatment Assignment Causal Inference Task Treatment Effect Estimation

November 12, 2021

ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects
Newton Mwai Kinyanjui, Fredrik D. Johansson
Alzheimer'S Disease Causal Effect Causal Effect Estimation Observational Data Causal Inference Task Heterogeneous Effect Diagnostic Reasoning Benchmark