Causal Relation

Causal relation research aims to identify and understand cause-and-effect relationships within data, moving beyond simple correlations to reveal underlying mechanisms. Current efforts focus on developing robust algorithms and models, including constraint-based methods, neural networks (like those employing Granger causality or score matching), and large language models (LLMs) for extracting causal information from text and other data sources. These advancements are crucial for various fields, enabling more accurate predictions, improved decision-making in areas like healthcare and policy, and a deeper understanding of complex systems across scientific disciplines. The integration of human expertise and background knowledge is also a growing focus, aiming to improve the reliability and interpretability of causal inferences.

Papers

April 1, 2024

March 11, 2024

Detection of Unobserved Common Causes based on NML Code in Discrete, Mixed, and Continuous Variables
Masatoshi Kobayashi, Kohei Miyagichi, Shin Matsushima
Data Detection Causal Discovery Causal Relationship Causal Relation Causal Discovery Method Discrete Environment Continuous Variable

February 6, 2024

Discovery of the Hidden World with Large Language Models
Chenxi Liu, Yongqiang Chen, Tongliang Liu, Mingming Gong, James Cheng, Bo Han, Kun Zhang
Scientific Discovery Causal Relation Causal Discovery Method Underlying Causal

December 22, 2023

Zero-shot Causal Graph Extrapolation from Text via LLMs
Alessandro Antonucci, Gregorio Piqué, Marco Zaffalon
Large Language Model Text Modality Causal Inference Causal Graph Causal Relation Causal View Ground Truth Causal Zero Shot Causal

December 18, 2023

Shapley-PC: Constraint-based Causal Structure Learning with Shapley Values
Fabrizio Russo, Francesca Toni
Causal Discovery Shapley Value Conditional Independence Causal Relation Causal Structure Learning

November 5, 2023

Causal Question Answering with Reinforcement Learning
Lukas Blübaum, Stefan Heindorf
Reinforcement Learning Causal Graph Causal Relationship Causal Relation Causal Query

September 30, 2023

Interpretable Imitation Learning with Dynamic Causal Relations
Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
Imitation Learning Causal Graph Causal Relation Latent Causal

September 21, 2023

Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets
Tiago da Silva, Eliezer Silva, António Góis, Dominik Heider, Samuel Kaski, Diego Mesquita, Adèle Ribeiro
Causal Inference Causal Discovery Causal Relation Energy Based GFlowNets Latent Confounding Causal Attribution Ancestral Graph

August 16, 2023

Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series
Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu
Graph Drawing Conditional Independence Causal Relation TV Show Topological Ordering

August 10, 2023

Shadow Datasets, New challenging datasets for Causal Representation Learning
Jiageng Zhu, Hanchen Xie, Jianhua Wu, Jiazhi Li, Mahyar Khayatkhoei, Mohamed E. Hussein, Wael AbdAlmageed
Representation Learning Causal Graph Causal Relation Causal Representation Learning Generative Factor Challenging Dataset Shadow Detection Datasets

July 31, 2023

Causal-learn: Causal Discovery in Python
Yujia Zheng, Biwei Huang, Wei Chen, Joseph Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang
Causal Discovery Causal Relation Causal Discovery Method Causal Learning

July 28, 2023

Case Studies of Causal Discovery from IT Monitoring Time Series
Ali Aït-Bachir, Charles K. Assaad, Christophe de Bignicourt, Emilie Devijver, Simon Ferreira, Eric Gaussier, Hosein Mohanna, Lei Zan
Case Study Causal Discovery Time Series Analysis Causal Relation Causal Discovery Algorithm

July 18, 2023

Non-stationary Delayed Combinatorial Semi-Bandit with Causally Related Rewards
Saeed Ghoorchian, Setareh Maghsudi
Sequential Decision Causal Relation Delayed Feedback Combinatorial Semi Bandit

July 13, 2023

Causal Influences over Social Learning Networks
Mert Kayaalp, Ali H. Sayed
Causal Relation Causal Variable Social Graph Network Learning Pre Specified Agent Specific

July 3, 2023

Identification of Causal Relationship between Amyloid-beta Accumulation and Alzheimer's Disease Progression via Counterfactual Inference
Haixing Dai, Mengxuan Hu, Qing Li, Lu Zhang, Lin Zhao, Dajiang Zhu, Ibai Diez, Jorge Sepulcre, Fan Zhang, Xingyu Gao, Manhua Liu, Quanzheng Li, Sheng Li, Tianming Liu, Xiang Li
Alzheimer'S Disease Causal Relationship Causal Relation Counterfactual Inference Amyloid Beta

June 19, 2023

On Identifiability of Conditional Causal Effects
Yaroslav Kivva, Jalal Etesami, Negar Kiyavash
Causal Effect Causal Relation Novel Identifiability Test Partial Identifiability Parameter Identifiability

June 15, 2023

June 1, 2023

From Temporal to Contemporaneous Iterative Causal Discovery in the Presence of Latent Confounders
Raanan Y. Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik
Causal Graph Causal Structure Speech Presence Temporal Information Causal Relation Latent Confounders