Causal Direction

Causal direction research aims to determine the cause-and-effect relationships between variables, moving beyond simple correlations to understand underlying mechanisms. Current research focuses on developing robust methods for causal discovery from observational data, often employing techniques like Bayesian networks, structural causal models, and graph neural networks, as well as leveraging large language models to extract causal information from text and data. This field is crucial for advancing scientific understanding across diverse disciplines and informing data-driven decision-making in areas such as healthcare, economics, and engineering, by enabling more accurate predictions and interventions.

Papers

February 13, 2024

Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation
Xuexin Chen, Ruichu Cai, Zhengting Huang, Yuxuan Zhu, Julien Horwood, Zhifeng Hao, Zijian Li, Jose Miguel Hernandez-Lobato
High Explainability Community Need Feature Attribution Attribution Method Causal Direction Counterfactual Reasoning Feature Attribution Method

February 3, 2024

Unveiling Latent Causal Rules: A Temporal Point Process Approach for Abnormal Event Explanation
Yiling Kuang, Chao Yang, Yang Yang, Shuang Li
Causal Direction Temporal Point Process Latent Causal Anomalous Data Rule Discovery

January 16, 2024

Deep Learning-based Group Causal Inference in Multivariate Time-series
Wasim Ahmad, Maha Shadaydeh, Joachim Denzler
Causal Inference Causal Structure Multivariate Time Series Causal Direction Deep Causal Causality Method

December 19, 2023

Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants
Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang
Causal Discovery Person Identification Latent Variable Causal Structure Causal Direction Order Cumulants Causal Parameter

December 14, 2023

Temporal-Spatial Entropy Balancing for Causal Continuous Treatment-Effect Estimation
Tao Hu, Honglong Zhang, Fan Zeng, Min Du, XiangKun Du, Yue Zheng, Quanqi Li, Mengran Zhang, Dan Yang, Jihao Wu
Causal Effect Treatment Effect Causal Direction Spatial Entropy

December 9, 2023

Multi-granularity Causal Structure Learning
Jiaxuan Liang, Jun Wang, Guoxian Yu, Shuyin Xia, Guoyin Wang
Causal Structure Causal Direction Causal Abstraction Causal Learning Algorithm

November 25, 2023

Exploring Causal Learning through Graph Neural Networks: An In-depth Review
Simi Job, Xiaohui Tao, Taotao Cai, Haoran Xie, Lin Li, Jianming Yong, Qing Li
Graph Neural Network Comprehensive Review Causal Relationship Causal Pattern Causal Direction Causal Learning Causality Analysis

November 15, 2023

Causal prediction models for medication safety monitoring: The diagnosis of vancomycin-induced acute kidney injury
Izak Yasrebi-de Kom, Joanna Klopotowska, Dave Dongelmans, Nicolette De Keizer, Kitty Jager, Ameen Abu-Hanna, Giovanni Cinà
Causal Inference Medical Diagnosis Causal Model Causal Direction Causal Prediction Causality Analysis Drug Safety Acute Kidney Injury

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 19, 2023

Bayesian Meta-Learning for Improving Generalizability of Health Prediction Models With Similar Causal Mechanisms
Sophie Wharrie, Lisa Eick, Lotta Mäkinen, Andrea Ganna, Samuel Kaski, FinnGen
High Similarity Causal Direction Cause Effect Hierarchical Model

October 9, 2023

Causal Reasoning through Two Layers of Cognition for Improving Generalization in Visual Question Answering
Trang Nguyen, Naoaki Okazaki
Strong Generalization Visual Question Answering Multi Layer Causal Direction Cognitive Learning Causal Reasoning

September 25, 2023

Frame-wise streaming end-to-end speaker diarization with non-autoregressive self-attention-based attractors
Di Liang, Nian Shao, Xiaofei Li
Causal Direction Neural Diarization Frame Consistency Attractor Network Speaker Attractor End to End Speaker Diarization

August 11, 2023

Towards a Causal Probabilistic Framework for Prediction, Action-Selection & Explanations for Robot Block-Stacking Tasks
Ricardo Cannizzaro, Jonathan Routley, Lars Kunze
Human Prediction Robot Person Line by Line Explanation Causal Inference Causal Model Real Robot Causal Direction Pick and Place Action Selection

July 11, 2023

Reducing Causality to Functions with Structural Models
Tianyi Miao
Causal Pattern Simple Function Multi Scenario Causal Direction Actual Cause Causal View Structure Based Model

June 5, 2023

Bivariate Causal Discovery using Bayesian Model Selection
Anish Dhir, Samuel Power, Mark van der Wilk
Causal Discovery Causal Direction Bayesian Model Selection Causal Assumption

May 31, 2023

Active causal structure learning with advice
Davin Choo, Themis Gouleakis, Arnab Bhattacharyya
Learning Algorithm Worst Case Causal Direction Advice Quality Temporal Causal Ancestral Graph

May 30, 2023

May 21, 2023

Discovering Causal Relations and Equations from Data
Gustau Camps-Valls, Andreas Gerhardus, Urmi Ninad, Gherardo Varando, Georg Martius, Emili Balaguer-Ballester, Ricardo Vinuesa, Emiliano Diaz, Laure Zanna, Jakob Runge
Raw Data Causal Relation Causal Direction Observational Data Diverse Equation Observational Causal

May 10, 2023

Causal Information Splitting: Engineering Proxy Features for Robustness to Distribution Shifts
Bijan Mazaheri, Atalanti Mastakouri, Dominik Janzing, Michaela Hardt
Native Robustness Distribution Shift Causal Direction Prediction Model Model Stability

Causal Direction

Papers

Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation

Unveiling Latent Causal Rules: A Temporal Point Process Approach for Abnormal Event Explanation

Deep Learning-based Group Causal Inference in Multivariate Time-series

Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants

Temporal-Spatial Entropy Balancing for Causal Continuous Treatment-Effect Estimation

Multi-granularity Causal Structure Learning

Exploring Causal Learning through Graph Neural Networks: An In-depth Review

Causal prediction models for medication safety monitoring: The diagnosis of vancomycin-induced acute kidney injury

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

Bayesian Meta-Learning for Improving Generalizability of Health Prediction Models With Similar Causal Mechanisms

Causal Reasoning through Two Layers of Cognition for Improving Generalization in Visual Question Answering

Frame-wise streaming end-to-end speaker diarization with non-autoregressive self-attention-based attractors

Towards a Causal Probabilistic Framework for Prediction, Action-Selection & Explanations for Robot Block-Stacking Tasks

Reducing Causality to Functions with Structural Models

Bivariate Causal Discovery using Bayesian Model Selection

Active causal structure learning with advice

dotears: Scalable, consistent DAG estimation using observational and interventional data

The Magic of IF: Investigating Causal Reasoning Abilities in Large Language Models of Code

Discovering Causal Relations and Equations from Data

Causal Information Splitting: Engineering Proxy Features for Robustness to Distribution Shifts