Causal System

Causal system research aims to understand and quantify cause-and-effect relationships, particularly within complex, dynamic systems where confounding factors obscure true influences. Current efforts focus on developing methods to infer causality from observational data, even in the presence of unobservable confounders, using techniques like delay embedding and interventional entropy, and employing model architectures such as causal autoencoders and Bayesian networks. These advancements are crucial for improving the reliability of causal inference across diverse fields, from biological networks and climate modeling to recommendation systems and reinforcement learning, enabling more accurate predictions and informed interventions.

Papers

November 12, 2024

Dynamical-VAE-based Hindsight to Learn the Causal Dynamics of Factored-POMDPs
Chao Han, Debabrota Basu, Michael Mangan, Eleni Vasilaki, Aditya Gilra
Markov Decision Process Hindsight Instruction Causal System Dynamical Variational Markovian Sequence

October 31, 2024

Average Controlled and Average Natural Micro Direct Effects in Summary Causal Graphs
Simon Ferreira, Charles K. Assaad
Causal Inference Causal Graph Causal Effect Causal System Average Performance Summary Causal Graph

October 25, 2024

LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data
Yue Cheng, Jiajun Zhang, Weiwei Xing, Xiaoyu Guo, Xiaohui Gao
Time Series Data Causal Learning Dynamic Graph Learning Causal System Rotation Matrix

October 7, 2024

Neural Networks Decoded: Targeted and Robust Analysis of Neural Network Decisions via Causal Explanations and Reasoning
Alec F. Diallo, Vaishak Belle, Paul Patras
Deep Learning Complex Reasoning Causal Inference Causal Graph Interpretability Method Causal Explanation Causal System Neural Network Decoder

August 10, 2024

Dynamical causality under invisible confounders
Jinling Yan, Shao-Wu Zhang, Chihao Zhang, Weitian Huang, Jifan Shi, Luonan Chen
Causal Inference Latent Confounders Event Causality Identification Causal System

June 29, 2024

Deciphering interventional dynamical causality from non-intervention systems
Jifan Shi, Yang Li, Juan Zhao, Siyang Leng, Kazuyuki Aihara, Luonan Chen, Wei Lin
Causal Pattern Dynamical Model Causal Effect Identification Causal System Causal Entropy

June 12, 2024

Interventional Causal Discovery in a Mixture of DAGs
Burak Varıcı, Dmitriy Katz-Rogozhnikov, Dennis Wei, Prasanna Sattigeri, Ali Tajer
Causal Discovery Mixture Component Causal Graph Causal Variable Causal System High Reward DAG Causal Structure Discovery

May 21, 2024

Learning Causal Dynamics Models in Object-Oriented Environments
Zhongwei Yu, Jingqing Ruan, Dengpeng Xing
Reinforcement Learning Causal Discovery Object Oriented Causal System Causal Dynamic Learning

October 11, 2023

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning
Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi
Reinforcement Learning Causal Graph Posterior Sampling Bayesian Regret Causal System

April 23, 2023

Meaningful Causal Aggregation and Paradoxical Confounding
Yuchen Zhu, Kailash Budhathoki, Jonas Kuebler, Dominik Janzing
Causal Pattern Causal Relation Cause Effect Causal System Q Aggregation Non Confounding Covariates

February 2, 2023

Disentanglement of Latent Representations via Causal Interventions
Gaël Gendron, Michael Witbrock, Gillian Dobbie
Latent Representation Disentanglement Capability Causal Representation Learning Causal Intervention Vector Quantized Variational Autoencoder Causal System

October 20, 2022

Causal Structural Hypothesis Testing and Data Generation Models
Jeffrey Jiang, Omead Pooladzandi, Sunay Bhat, Gregory Pottie
Structural Prior Causal System Variational Causal Data Generation Model

October 19, 2022

Causal Structure Learning with Recommendation System
Shuyuan Xu, Da Xu, Evren Korpeoglu, Sushant Kumar, Stephen Guo, Kannan Achan, Yongfeng Zhang
Causal Structure Structural Causal Model Causal Structure Learning Causal System

July 25, 2022

Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation
Alex Andrew, Sam Spillard, Joshua Collyer, Neil Dhir
Causal Model Bayesian Optimisation Cyber Defense Causal System

July 18, 2022

Abstraction between Structural Causal Models: A Review of Definitions and Properties
Fabio Massimo Zennaro
Narrative Review Structural Causal Model Many Property Definition Defining Redefinition Cognitive Abstraction Metric Aware Abstraction Causal Abstraction Causal System Analysis Formalism

June 30, 2022

A Causal Approach to Detecting Multivariate Time-series Anomalies and Root Causes
Wenzhuo Yang, Kun Zhang, Steven C. H. Hoi
Causal Pattern Root Cause Detecting Anomaly Multivariate Time Series Anomaly Detection Causal Approach Causal System Local Effect

June 27, 2022

Causal Dynamics Learning for Task-Independent State Abstraction
Zizhao Wang, Xuesu Xiao, Zifan Xu, Yuke Zhu, Peter Stone
Model Based Reinforcement Learning Learned Dynamic State Abstraction Causal System Causal Dynamic Learning

April 28, 2022

CKH: Causal Knowledge Hierarchy for Estimating Structural Causal Models from Data and Priors
Riddhiman Adib, Md Mobasshir Arshed Naved, Chih-Hao Fang, Md Osman Gani, Ananth Grama, Paul Griffin, Sheikh Iqbal Ahamed, Mohammad Adibuzzaman
Raw Data Causal Model Structural Causal Model SAM Prior Causal System Causal Hierarchy

March 9, 2022

Revealing the Excitation Causality between Climate and Political Violence via a Neural Forward-Intensity Poisson Process
Schyler C. Sun, Bailu Jin, Zhuangkun Wei, Weisi Guo
Climate Domain Causal System Conflict Dynamic

December 8, 2021

Non parametric estimation of causal populations in a counterfactual scenario
Celine Beji, Florian Yger, Jamal Atif
Latent Space Variational Autoencoder Causal Pattern Parameter Estimation Causal System Unseen Test Distribution