Causal Discovery Method

Causal discovery methods aim to infer cause-and-effect relationships from data, a crucial task for understanding complex systems. Current research emphasizes improving the scalability and efficiency of existing algorithms like LiNGAM, developing novel approaches such as those based on neural networks (e.g., transformers, graph neural networks) and optimal transport, and addressing challenges like handling temporal dependencies, high dimensionality, missing data, and unobserved confounders. These advancements are significantly impacting various fields, enabling more robust causal inference in applications ranging from healthcare and finance to robotics and environmental science.

Papers

May 10, 2023

CUTS+: High-dimensional Causal Discovery from Irregular Time-series
Yuxiao Cheng, Lianglong Li, Tingxiong Xiao, Zongren Li, Qin Zhong, Jinli Suo, Kunlun He
Causal Discovery Causal Graph Causal Discovery Method Causal Structure Learning Cut and Approximate Irregular Time Series High Dimensional Causal

April 12, 2023

DiscoGen: Learning to Discover Gene Regulatory Networks
Nan Rosemary Ke, Sara-Jane Dunn, Jorg Bornschein, Silvia Chiappa, Melanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane Wang, Theophane Weber, David Barrett, Matthew Botvinick, Anirudh Goyal, Mike Mozer, Danilo Rezende
Causal Discovery Causal Discovery Method Regulatory Network Genetic Network

April 6, 2023

Causal Discovery with Score Matching on Additive Models with Arbitrary Noise
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
Causal Discovery Causal Graph Score Matching Causal Discovery Method Additive Model Causal Discovery Algorithm Noise Distribution

April 5, 2023

A step towards the applicability of algorithms based on invariant causal learning on observational data
Borja Guerrero Santillan
Practical Algorithm Causal Inference Causal Discovery Observational Data Causal Discovery Method Sample STEP Applicability Study Optimal Prediction Invariant Causal Feature Invariant Causal

March 27, 2023

A Survey on Causal Discovery Methods for I.I.D. and Time Series Data
Uzma Hasan, Emam Hossain, Md Osman Gani
Timely Survey Causal Discovery Time Series Data Causal Relation Causal Discovery Method Cause Effect Causal Discovery Algorithm

March 17, 2023

Causal Discovery from Temporal Data: An Overview and New Perspectives
Chang Gong, Di Yao, Chuzhe Zhang, Wenbin Li, Jingping Bi
Causal Discovery New Perspective Temporal Data Causal Discovery Method Temporal Causal Discovery

February 7, 2023

CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series Data
Muhammad Hasan Ferdous, Uzma Hasan, Md Osman Gani
Time Series Causal Discovery Causal Relationship Causal Relation Causal Discovery Method Constraint Based Causal Discovery Temporal Causal Discovery

January 31, 2023

Evaluating Temporal Observation-Based Causal Discovery Techniques Applied to Road Driver Behaviour
Rhys Howard, Lars Kunze
Causal Discovery Method Temporal Pattern Autonomous Driving Domain Observational Causal Multi Scene

November 23, 2022

Causal Analysis of the TOPCAT Trial: Spironolactone for Preserved Cardiac Function Heart Failure
Francesca E. D. Raimondi, Tadhg O'Keeffe, Hana Chockler, Andrew R. Lawrence, Tamara Stemberga, Andre Franca, Maksim Sipos, Javed Butler, Shlomo Ben-Haim
Causal Discovery Causal Effect Causal Analysis Causal Discovery Method Multi Center Study Heart Failure

November 7, 2022

Federated Causal Discovery From Interventions
Amin Abyaneh, Nino Scherrer, Patrick Schwab, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou
Causal Discovery Causal Structure Heterogeneous Treatment Effect Causal Discovery Method Health Intervention Federated Causal

October 29, 2022

Causal Discovery of Dynamic Models for Predicting Human Spatial Interactions
Luca Castri, Sariah Mghames, Marc Hanheide, Nicola Bellotto
Human Robot Interaction Causal Discovery Causal Model Dynamic Model Causal Discovery Method Causal Discovery Algorithm Temporal Interaction

October 26, 2022

Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise
Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski
Causal Relationship Causal Discovery Method Causal Categorization Historical Robot Rhino

October 12, 2022

Diffusion Models for Causal Discovery via Topological Ordering
Pedro Sanchez, Xiao Liu, Alison Q O'Neil, Sotirios A. Tsaftaris
Diffusion Model Causal Discovery Causal Graph Causal Relation Causal Discovery Method Topological Ordering

September 14, 2022

A Review and Roadmap of Deep Learning Causal Discovery in Different Variable Paradigms
Hang Chen, Keqing Du, Xinyu Yang, Chenguang Li
Causal Discovery Causal Discovery Method Requirement Based Roadmap Explanatory Paradigm Causal Discovery Task

June 16, 2022

Empirical Bayesian Approaches for Robust Constraint-based Causal Discovery under Insufficient Data
Zijun Cui, Naiyu Yin, Yuru Wang, Qiang Ji
Causal Discovery Limited Data Causal Discovery Method Cause Effect Empirical Bayes Constraint Based Causal Discovery Frequentist Inference

June 3, 2022

BaCaDI: Bayesian Causal Discovery with Unknown Interventions
Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause
Causal Structure Causal Discovery Method Unknown Intervention Synthetic Causal

May 27, 2022

MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models
Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard Bondell
Causal Discovery Speech Presence Imputation Algorithm Causal Discovery Method Missing Data Additive Noise

March 29, 2022

Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data
Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszár
Causal Discovery Person Identification Causal Structure Conditional Independence Causal Discovery Method Causal Discovery Algorithm Invariant Causal Feature De Finetti

March 8, 2022

Score matching enables causal discovery of nonlinear additive noise models
Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russel, Bernhard Schölkopf, Dominik Janzing, Francesco Locatello
Causal Discovery Causal Graph Score Matching Causal Discovery Method Additive Noise

January 14, 2022

Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions
Ignavier Ng, Yujia Zheng, Jiji Zhang, Kun Zhang
Causal Discovery Causal Discovery Method Score Based Efficient Search Bayesian Network Structure Structure Estimation