Scientific Machine Learning of Chaotic Systems Learns Reduced-Order Equations for Neural Populations
PEM-UDE, a method that combines prediction-error methodology with universal differential equations to discover governing equations from limited, noise-corrupted observations, yields a multi-scale neural mass model that ties single-neuron parameters to macroscopic network dynamics and predicts a relationship between con...
Anthony G. Chesebro, David Hofmann, V. Dixit et al.
· 1 citation