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Found 4 papers, 3 papers with code
Detecting structural perturbations from time series with deep learning
Small disturbances can trigger functional breakdowns in complex systems.
Deep learning of contagion dynamics on complex networks
Forecasting the evolution of contagion dynamics is still an open problem to which mechanistic models only offer a partial answer.
Phase transition in the recoverability of network history
Network growth processes can be understood as generative models of the structure and history of complex networks.
Finite size analysis of the detectability limit of the stochastic block model
We then distinguish the concept of average detectability from the concept of instance-by-instance detectability and give explicit formulas for both definitions.
Physics and Society Information Theory Information Theory
