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Found 3 papers, 2 papers with code
A data-informed mean-field approach to mapping of cortical parameter landscapes
Constraining the many biological parameters that govern cortical dynamics is computationally and conceptually difficult because of the curse of dimensionality.
Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism
Model reduction methods aim to describe complex dynamic phenomena using only relevant dynamical variables, decreasing computational cost, and potentially highlighting key dynamical mechanisms.
Control Theory and Experimental Design in Diffusion Processes
We propose to accomplish this with a two-step strategy: when the full state vector of the diffusion process is observable continuously, we formulate this as an optimal control problem and apply numerical techniques from stochastic optimal control to solve it.
Methodology
