Causal Order

Causal order, the sequence in which variables influence each other, is crucial for understanding complex systems and making reliable causal inferences from observational data. Current research focuses on developing robust algorithms and model architectures, such as those based on additive noise models, fixed-point approaches, and boosting methods, to infer causal order even with limited or noisy data, including scenarios with unobserved variables or high dimensionality. These advancements are improving the accuracy and efficiency of causal discovery, impacting fields ranging from biology and neuroscience to economics and engineering through more reliable causal modeling and improved decision-making. The integration of large language models is also being explored to enhance causal order discovery, particularly in text-based data analysis.

Papers

October 24, 2024

Causal Order Discovery based on Monotonic SCMs
Ali Izadi, Martin Ester
Causal Inference Causal Discovery Structural Causal Model Causal Order

October 11, 2024

Efficient Differentiable Discovery of Causal Order
Mathieu Chevalley, Arash Mehrjou, Patrick Schwab
Auxiliary Sorting Network Rearranges Causal Discovery Algorithm Causal Order Causal Ordering Differentiable Causal Discovery

September 28, 2024

How much do we really know about Structure Learning from i.i.d. Data? Interpretable, multi-dimensional Performance Indicator for Causal Discovery
Georg Velev, Stefan Lessmann
Raw Data Causal Discovery Structure Learning Causal Order Multi Dimensional Evaluation

August 30, 2024

Towards Definition of Higher Order Causality in Complex Systems
Jakub Kořenek, Pavel Sanda, Jaroslav Hlinka
Definition Defining Redefinition Complex System Causal Variable Causal Network Pairwise Interaction Causal Order

May 28, 2024

Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
Mathieu Chevalley, Patrick Schwab, Arash Mehrjou
Practical Algorithm Causal Inference Causal Structure Learning Formal Guarantee Causal Order Causal Ordering Interventional Data

April 10, 2024

FiP: a Fixed-Point Approach for Causal Generative Modeling
Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang, Chao Ma
Causal Structure Structural Causal Model Two Stage Fixed Point Causal Order Causal Generative

March 29, 2024

MambaMixer: Efficient Selective State Space Models with Dual Token and Channel Selection
Ali Behrouz, Michele Santacatterina, Ramin Zabih
Vision Model Attention Module Selective State Space Model Causal Order Channel Selection

March 25, 2024

Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis
Jie Qiao, Yu Xiang, Zhengming Chen, Ruichu Cai, Zhifeng Hao
Causal Discovery Causal Structure Structural Causal Model Path Modeling Poisson Noise Causal Order

February 22, 2024

January 12, 2024

Boosting Causal Additive Models
Maximilian Kertel, Nadja Klein
Structural Equation Boosting Algorithm Causal Order Causal Ordering

October 23, 2023

Causal Inference Using LLM-Guided Discovery
Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N Balasubramanian, Amit Sharma
Causal Inference Causal Graph Causal Discovery Algorithm Causal Order

August 20, 2023

Karma: Adaptive Video Streaming via Causal Sequence Modeling
Bowei Xu, Hao Chen, Zhan Ma
Video Streaming Causal Order Adaptive Bitrate Monetary Reward

August 5, 2023

Physics-Based Task Generation through Causal Sequence of Physical Interactions
Chathura Gamage, Vimukthini Pinto, Matthew Stephenson, Jochen Renz
Physic Based Physical Reasoning Physical Simulation Physical Interaction Causal Order

July 21, 2023

Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues
Antonio Orvieto, Soham De, Caglar Gulcehre, Razvan Pascanu, Samuel L. Smith
\Sigma}{\Delta}$ Low Pas RNN K$ Universality Smallest Eigenvalue Causal Order Linear RNN Recurrence Relation

March 31, 2023

A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models
Alexander G. Reisach, Myriam Tami, Christof Seiler, Antoine Chambaz, Sebastian Weichwald
Causal Discovery Additive Noise Scale Invariant Causal Order

August 14, 2022

Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables
Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash
Constructive Approach Speech Presence Long Form Novel Structure Learning Causal Structure Learning Unobserved Variable Markov Equivalence Class Causal Order Ancestral Graph

May 11, 2022

Causal discovery under a confounder blanket
David S. Watson, Ricardo Silva
Causal Discovery Causal Relationship Unobserved Confounders Causal Discovery Algorithm Causal Order

November 3, 2021

Multi-task Learning of Order-Consistent Causal Graphs
Xinshi Chen, Haoran Sun, Caleb Ellington, Eric Xing, Le Song
Multi Task Learning Graph Structure Directed Acyclic Graph Structural Equation Causal Order