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Found 2 papers, 2 papers with code
Deep Random Splines for Point Process Intensity Estimation of Neural Population Data
Gaussian processes are the leading class of distributions on random functions, but they suffer from well known issues including difficulty scaling and inflexibility with respect to certain shape constraints (such as nonnegativity).
Using Firing-Rate Dynamics to Train Recurrent Networks of Spiking Model Neurons
Recurrent neural networks are powerful tools for understanding and modeling computation and representation by populations of neurons.
Neurons and Cognition
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