Causal Pattern

Causal pattern research aims to identify and quantify cause-and-effect relationships within complex systems, moving beyond simple correlations to understand underlying mechanisms. Current research focuses on developing and applying methods like structural causal models, Granger causality, and various machine learning techniques (e.g., sparse regression, GNNs) to uncover causal patterns in diverse data types, including time series, tabular data, and even images. This work has significant implications for various fields, improving the reliability and interpretability of models in areas such as healthcare, agriculture, finance, and autonomous systems by enabling more robust predictions and informed decision-making.

Papers

August 19, 2022

July 26, 2022

XInsight: eXplainable Data Analysis Through The Lens of Causality
Pingchuan Ma, Rui Ding, Shuai Wang, Shi Han, Dongmei Zhang
Causal Graph Camera Lens Causal Pattern Exploratory Data Analysis Quantitative Explanation

July 8, 2022

On the Need and Applicability of Causality for Fair Machine Learning
Rūta Binkytė, Ljupcho Grozdanovski, Sami Zhioua
Procedural Fairness Causal Pattern Community Need Fair Machine Learning Fairness Evaluation Applicability Study Causal Prediction Causal View

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 29, 2022

Causality for Inherently Explainable Transformers: CAT-XPLAIN
Subash Khanal, Benjamin Brodie, Xin Xing, Ai-Ling Lin, Nathan Jacobs
Causal Pattern Post Hoc Explanation Explainable Model Post Hoc

June 27, 2022

Geo-Situation for Modeling Causality of Geo-Events in Knowledge Graphs
Shirly Stephen, Wenwen Li, Torsten Hahmann
Knowledge Graph Causal Pattern Geo Event

June 11, 2022

A Review of Causality for Learning Algorithms in Medical Image Analysis
Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz
Medical Image Analysis Medical Imaging Causal Pattern Learning Algorithm Causal Analysis Causality Method

May 10, 2022

On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis for Parametric Models
Xuetong Wu, Mingming Gong, Jonathan H. Manton, Uwe Aickelin, Jingge Zhu
Domain Adaptation Semi Supervised Learning Unsupervised Domain Adaptation Causal Pattern Causal Learning Cause Effect Causal Prediction

May 5, 2022

Action Languages Based Actual Causality for Computational Ethics: a Sound and Complete Implementation in ASP
Camilo Sarmiento, Gauvain Bourgne, Katsumi Inoue, Daniele Cavalli, Jean-Gabriel Ganascia
Causal Pattern Logic Programming Cause Effect Implementation Detail Actual Causality Machine Ethic Language Action

April 4, 2022

Causality, Causal Discovery, and Causal Inference in Structural Engineering
M. Z. Naser
Causal Inference Causal Discovery Causal Model Causal Pattern Causal Approach Structural Engineering Causal Concept

April 2, 2022

Model-Free and Model-Based Policy Evaluation when Causality is Uncertain
David Bruns-Smith
Causal Effect Policy Evaluation Causal Pattern Model Free Unobserved Confounders Uncertain Reasoning

April 1, 2022

From Statistical to Causal Learning
Bernhard Schölkopf, Julius von Kügelgen
Machine Learning Artificial Intelligence Causal Pattern Causal Learning Intelligent System Symbolic Approach

March 29, 2022

Finding Structure and Causality in Linear Programs
Matej Zečević, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting
Machine Learning Causal Pattern Linear Programming End to End Learning Inference Problem Structure Discovery

March 14, 2022

Respecting causality is all you need for training physics-informed neural networks
Sifan Wang, Shyam Sankaran, Paris Perdikaris
Physic Informed Neural Network Causal Pattern Chaotic Regime Stratified Turbulence Actual Causality Chaotic Lorenz

February 20, 2022

Trying to Outrun Causality with Machine Learning: Limitations of Model Explainability Techniques for Identifying Predictive Variables
Matthew J. Vowels
Machine Learning Causal Structure Fundamental Limitation Causal Pattern Underlying Causal Explainability Technique Causal Objective Function

February 12, 2022

Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning
Sebastian Weichwald, Søren Wengel Mogensen, Tabitha Edith Lee, Dominik Baumann, Oliver Kroemer, Isabelle Guyon, Sebastian Trimpe, Jonas Peters, Niklas Pfister
Reinforcement Learning LeArning Abstract External Control Dynamical System Causal Structure Causal Pattern

February 3, 2022

Sequentially learning the topological ordering of causal directed acyclic graphs with likelihood ratio scores
Gabriel Ruiz, Oscar Hernan Madrid Padilla, Qing Zhou
Causal Discovery Causal Pattern Single Cell Causal Direction Novel Identifiability Test Likelihood Ratio Topological Ordering

January 30, 2022

Discovering Invariant Rationales for Graph Neural Networks
Ying-Xin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua
Graph Neural Network Inherent Interpretability Causal Pattern Interpretable Graph Neural Network

January 26, 2022

Promises and Challenges of Causality for Ethical Machine Learning
Aida Rahmattalabi, Alice Xiang
Technical Challenge Causal Inference Causal Pattern Promise Responsible Machine Learning Causal Fairness