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Causality and Complex Systems

Complex systems are unified wholes formed by many interacting units. One key source of their complexity lies in the intricate entanglement of causal structures. A notable feature of these systems is the phenomenon of emergent causality, where stronger causal relationships may arise at the macro-scal...

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Format: Online
Sprog:engelsk
Udgivet: MDPI - Multidisciplinary Digital Publishing Institute 2026
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Causal emergence
Coarse-graining
Invertible neural network
Emergence
Causality
Higher-order interaction
Partial information decomposition
Synergy
Networks
Neuroscience
Information geometry
Transfer Entropy
Granger Causality
Information causal rate
Signal processing
Nonlinear models
Non-stationary
Probability distribution
Environmental factors
Respiratory infection
Nonlinear system
Kernel Granger causality
Effective network
Schizophrenia MEG
Nonequilibrium
Complexity
Causal analysis
Granger causality
Bootstrap methods
Multivariate time series
Impulse response function
Aristotle
Causation
Causal closure
Downwards causation
N
A
Causal representation learning
Video prediction
Transfer learning
Few-shot learning
Causal discovery
Independence tests
Functional data analysis
Kernel methods
Direction of information flow
Transfer entropy
Anticipatory dynamics
Zebrafish
Causal inference
Maximizing mutual information
Unobserved causes
Complex system
Causal emergence identification
Effective information
Machine learning
Linear stochastic iteration system
Berkson’s paradox
Multivariate information theory
Higher-order interactions
Model-free
Data-driven
Nonlinear dynamics
Team dynamics
Information theory
Graph theory
Football analytics
Collective behavior
thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
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