Causal Analysis

Causal analysis aims to uncover cause-and-effect relationships within complex systems, moving beyond mere correlations to understand underlying mechanisms. Current research emphasizes developing robust methods for causal discovery and inference from observational data, often employing machine learning techniques like Bayesian networks, double machine learning, and structural causal models, as well as adapting these methods for high-dimensional data and time series. This field is crucial for advancing scientific understanding across diverse disciplines and informing decision-making in areas such as healthcare, economics, and AI development, by enabling more reliable predictions and interventions.

Papers

December 9, 2023

Causal-CoG: A Causal-Effect Look at Context Generation for Boosting Multi-modal Language Models
Shitian Zhao, Zhuowan Li, Yadong Lu, Alan Yuille, Yan Wang
Multimodal Model Causal Analysis Multi Modal Language Model Contextual Knowledge Context Generation Structural Causal Game

October 24, 2023

CR-COPEC: Causal Rationale of Corporate Performance Changes to Learn from Financial Reports
Ye Eun Chun, Sunjae Kwon, Kyunghwan Sohn, Nakwon Sung, Junyoup Lee, Byungki Seo, Kevin Compher, Seung-won Hwang, Jaesik Choi
MAESTRO Dataset Causal Direction Causal Analysis Causal Reasoning Financial Report Causal Domain Adaptation

October 23, 2023

Efficient Causal Discovery for Robotics Applications
Luca Castri, Sariah Mghames, Nicola Bellotto
Real World Human Robot Interaction Causal Discovery Causal Model Causal Analysis Robotics Application Novel Causal Model

October 17, 2023

Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs
Stelios Triantafyllou, Aleksa Sukovic, Debmalya Mandal, Goran Radanovic
Multi Agent Causal Effect Causal Analysis Multi Agent Decision Multi Agent Sequential Decision

October 14, 2023

A Framework for Empowering Reinforcement Learning Agents with Causal Analysis: Enhancing Automated Cryptocurrency Trading
Rasoul Amirzadeh, Dhananjay Thiruvady, Asef Nazari, Mong Shan Ee
Reinforcement Learning New Framework Causal Analysis Cryptocurrency Price Causal Machine Automated Cryptocurrency Trading Intelligent Trading

September 22, 2023

OpportunityFinder: A Framework for Automated Causal Inference
Huy Nguyen, Prince Grover, Devashish Khatwani
New Framework Causal Inference Emerging Opportunity Causal Effect Causal Analysis Causal Effect Identification

September 11, 2023

Using causal inference to avoid fallouts in data-driven parametric analysis: a case study in the architecture, engineering, and construction industry
Xia Chen, Ruiji Sun, Ueli Saluz, Stefano Schiavon, Philipp Geyer
Case Study Data Driven Causal Inference Architecture Design Causal Analysis Data Driven Model Position Engineering Data Driven Modeling

August 24, 2023

Machine Unlearning for Causal Inference
Vikas Ramachandra, Mohit Sethi
Causal Inference Machine Unlearning Causal Analysis Propensity Score

July 31, 2023

No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging
Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro, Ozan Oktay, Melissa McCradden, Ben Glocker
Machine Learning Medical Imaging Algorithmic Bias Causal Analysis Dataset Bias

June 20, 2023

PyRCA: A Library for Metric-based Root Cause Analysis
Chenghao Liu, Wenzhuo Yang, Himanshu Mittal, Manpreet Singh, Doyen Sahoo, Steven C. H. Hoi
Causal Graph Easy to Use Library Root Cause Causal Analysis Causal Discovery Method

June 7, 2023

On the Use of Generative Models in Observational Causal Analysis
Nimrod Megiddo
Generative Model Greater Public Use Causal Relationship Observational Data Causal Analysis Probabilistic Generative Model Joint Distribution Observational Causal

May 15, 2023

April 23, 2023

Improved Churn Causal Analysis Through Restrained High-Dimensional Feature Space Effects in Financial Institutions
David Hason Rudd, Huan Huo, Guandong Xu
Causal Analysis High Dimensional Feature Churn Prediction Customer Churn

April 20, 2023

Causal Analysis of Customer Churn Using Deep Learning
David Hason Rudd, Huan Huo, Guandong Xu
Deep Learning Causal Analysis Churn Prediction Customer Retention Customer Churn

April 8, 2023

Multi-class Categorization of Reasons behind Mental Disturbance in Long Texts
Muskan Garg
Mental Health Social Medium Data Reason Giving Multi Class Classification Causal Analysis Long Text Causal Categorization Explainable Causal

April 6, 2023

A Bayesian Framework for Causal Analysis of Recurrent Events with Timing Misalignment
Arman Oganisian, Anthony Girard, Jon A. Steingrimsson, Patience Moyo
Speech Presence Causal Analysis Recurrent Event Recurrence Relation

March 4, 2023

Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders
Defu Cao, James Enouen, Yujing Wang, Xiangchen Song, Chuizheng Meng, Hao Niu, Yan Liu
Treatment Effect Causal Analysis Unobserved Confounders Irregular Time Series

January 26, 2023

NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media
Muskan Garg, Chandni Saxena, Usman Naseem, Bonnie J Dorr
Natural Language Processing Social Medium Mental Health Causal Analysis Perception Model Scientific Synthesis Causal Relation Extraction

January 25, 2023

Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data
Devansh Arpit, Matthew Fernandez, Itai Feigenbaum, Weiran Yao, Chenghao Liu, Wenzhuo Yang, Paul Josel, Shelby Heinecke, Eric Hu, Huan Wang, Stephen Hoi, Caiming Xiong, Kun Zhang, Juan Carlos Niebles
Time Series Causal Inference Causal Discovery Tabular Data Causal Analysis Causal Machine Ground Truth Causal

Causal Analysis

Papers

Causal-CoG: A Causal-Effect Look at Context Generation for Boosting Multi-modal Language Models

CR-COPEC: Causal Rationale of Corporate Performance Changes to Learn from Financial Reports

Efficient Causal Discovery for Robotics Applications

Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs

A Framework for Empowering Reinforcement Learning Agents with Causal Analysis: Enhancing Automated Cryptocurrency Trading

OpportunityFinder: A Framework for Automated Causal Inference

Using causal inference to avoid fallouts in data-driven parametric analysis: a case study in the architecture, engineering, and construction industry

Machine Unlearning for Causal Inference

No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging

PyRCA: A Library for Metric-based Root Cause Analysis

On the Use of Generative Models in Observational Causal Analysis

Causal Analysis for Robust Interpretability of Neural Networks

Estimating the Causal Effects of Natural Logic Features in Neural NLI Models

Improved Churn Causal Analysis Through Restrained High-Dimensional Feature Space Effects in Financial Institutions

Causal Analysis of Customer Churn Using Deep Learning

Multi-class Categorization of Reasons behind Mental Disturbance in Long Texts

A Bayesian Framework for Causal Analysis of Recurrent Events with Timing Misalignment

Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders

NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media

Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data