Causal Relationship

Causal relationship research aims to understand and model cause-and-effect relationships within complex systems, moving beyond simple correlations. Current research focuses on developing algorithms and models, such as Bayesian networks, that can effectively learn causal structures from observational and interventional data, often incorporating expert knowledge or handling high-dimensional and incomplete datasets. These advancements are crucial for improving decision-making in various fields, including healthcare, finance, and robotics, by enabling more accurate predictions and interventions based on a deeper understanding of underlying causal mechanisms. The development of robust benchmarking frameworks further enhances the reliability and reproducibility of causal discovery methods.

Papers

March 3, 2024

The Implicit Bias of Heterogeneity towards Invariance and Causality
Yang Xu, Yihong Gu, Cong Fang
Causal Relationship Causal Pattern Implicit Bias Alpha Invariance Causal Knowledge

February 14, 2024

A Dynamical View of the Question of Why
Mehdi Fatemi, Sindhu Gowda
Yes No Question Causal Relationship Stochastic Process Dynamical Model

February 5, 2024

Counterfactual Explanations of Black-box Machine Learning Models using Causal Discovery with Applications to Credit Rating
Daisuke Takahashi, Shohei Shimizu, Takuma Tanaka
Financial Application Causal Discovery Counterfactual Explanation Causal Graph Causal Structure Causal Relationship Causal Discovery Method Credit Scoring Black Box Machine Learning Model

February 2, 2024

Efficient Causal Graph Discovery Using Large Language Models
Thomas Jiralerspong, Xiaoyin Chen, Yash More, Vedant Shah, Yoshua Bengio
Causal Graph Causal Relationship Causal Graph Discovery

January 31, 2024

Causal Discovery by Kernel Deviance Measures with Heterogeneous Transforms
Tim Tse, Zhitang Chen, Shengyu Zhu, Yue Liu
Causal Discovery Causal Relationship Cause Effect Heterogeneous Transformer Kernel Distance

January 24, 2024

Causal Relationship Network of Risk Factors Impacting Workday Loss in Underground Coal Mines
Shangsi Ren, Cameron A. Beeche, Zhiyi Shi, Maria Acevedo Garcia, Katherine Zychowski, Shuguang Leng, Pedram Roghanchi, Jiantao Pu
Causal Relationship Causal Network Task Loss

January 20, 2024

Interactive and Intelligent Root Cause Analysis in Manufacturing with Causal Bayesian Networks and Knowledge Graphs
Christoph Wehner, Maximilian Kertel, Judith Wewerka
Knowledge Graph Causal Relationship Root Cause Interactive No Code Manufacturing Industry Causal Bayesian Network

January 16, 2024

Towards Causal Relationship in Indefinite Data: Baseline Model and New Datasets
Hang Chen, Xinyu Yang, Keqing Du
Causal Discovery Causal Structure Causal Relationship Baseline Model New Datasets Multiple Representation

January 12, 2024

Deep Learning With DAGs
Sourabh Balgi, Adel Daoud, Jose M. Peña, Geoffrey T. Wodtke, Jesse Zhou
Deep Learning Causal Inference Causal Effect Causal Relationship Directed Acyclic Graph Parametric Causal Graphical Normalizing Flow

December 26, 2023

Review on Causality Detection Based on Empirical Dynamic Modeling
Cao Zhihao, Qu Hongchun
Narrative Review Causal Relationship Total Correlation Dynamic Modeling Causality Detection

December 23, 2023

An Explainable AI Approach to Large Language Model Assisted Causal Model Auditing and Development
Yanming Zhang, Brette Fitzgibbon, Dino Garofolo, Akshith Kota, Eric Papenhausen, Klaus Mueller
Causal Inference Development Activity Causal Model Causal Relationship Causal Language Causal Network Explainable AI Approach

December 15, 2023

Rethinking Causal Relationships Learning in Graph Neural Networks
Hang Gao, Chengyu Yao, Jiangmeng Li, Lingyu Si, Yifan Jin, Fengge Wu, Changwen Zheng, Huaping Liu
Graph Neural Network Causal Relationship Causal Learning Novel Causal Model Causal Categorization

December 11, 2023

BoschAI @ Causal News Corpus 2023: Robust Cause-Effect Span Extraction using Multi-Layer Sequence Tagging and Data Augmentation
Timo Pierre Schrader, Simon Razniewski, Lukas Lange, Annemarie Friedrich
Data Augmentation Causal Relationship Causal Pattern Event Causality Identification Sequence Tagging Sequence Tagging Model Causal News Corpus

December 10, 2023

Consciousness as a logically consistent and prognostic model of reality
Evgenii Vityaev
Real World Causal Model Causal Relationship Perception Aware Human Consciousness Prognostic Model

November 28, 2023

Recognizing Conditional Causal Relationships about Emotions and Their Corresponding Conditions
Xinhong Chen, Zongxi Li, Yaowei Wang, Haoran Xie, Jianping Wang, Qing Li
Causal Effect Causal Relationship Experienced Emotion Sufficient Condition Clause Recommendation

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 21, 2023

Causality is all you need
Ning Xu, Yifei Gao, Hongshuo Tian, Yongdong Zhang, An-An Liu
Causal Graph Causal Relationship Causal Pattern Causal Strength

November 17, 2023

Stable Differentiable Causal Discovery
Achille Nazaret, Justin Hong, Elham Azizi, David Blei
Causal Relationship Differentiable Causal Discovery Sparse Causal

November 13, 2023