The way to quantify emergence
Causal Emergence Community
Causal emergence and self reference
Swarma Club Reading Group Season.No1
This reading group aims to explore the relationship between causality, emergence, self-reference, integrated information theory, multi-scale, and other related topics.
Causal emergence and machine learning
Swarma Club Reading Group Season.No2
This reading group aims to sort out the relationship between causality, emergence, machine learning, information decomposition, and coarse-graining.
Causal emergence identification in complex systems
@ Jiang Zhang
Exploring the origins of causal emergence from uncertainty perspective
Roundtable discussion: Technical roadmap of causal emergence
@ Peng Cui ,Yongchao Duan, et al
Causal Model Discovery with Algorithmic Information Dynamics
@ Hector Zenil
The basic mechanisms of downward causation that allow causal emergence
@ George F. R. Ellis
An framework for effectively measuring the causal emergence (TBC)
@ Erik Hoel
We aim to explore the relationship between causality and complex systems and to develop a technical roadmap for causal emergence with a view to future development.
The conference time is from 14:00pm to 20:00pm on March 27th, Beijing
Associate Professor of the Tsinghua University
Professor of the Beijing Normal University
Founder and director of JITRI Institute of Deep Perception Technology
Professor of the Cape Town University
American neuroscientist, neurophilosopher and fiction writer
Co-leader of the Algorithmic Dynamics Lab at the Karolinska Institute; Senior researcher, Machine Learning Group, Department of Chemical Engineering and Biotechnology, University of Cambridge; and Founder and Director of Oxford Immune Algorithmics
Entropy Special Issue
"Causality and Complex Systems"
This Special Issue focuses on, but is not limited to, the following topics:Causal discovery, Causal inference, Causal emergence, Downward causality, Measures of complexity and causality, Complex system modeling, Causal machine learning, Causal representation learning, Causal reinforcement learning, Information decomposition and Related applications.
Special Issue Editors
Department of CS Tsinghua University, Interests: stable learning; information theory;
causality; GNN; network embedding
Special Issue Editors
School of Systems Sciences, Beijing Normal University,
Interests: complex systems; machine learning; causal emergence; scaling theory