Approximating nonlinear functions with latent boundaries in low-rank excitatory-inhibitory spiking networks.
William F. PodlaskiChristian K. MachensPublished in: CoRR (2023)
Keyphrases
- low rank
- spiking neural networks
- nonlinear functions
- rbf network
- spiking neurons
- biologically inspired
- neural network
- linear combination
- feed forward
- convex optimization
- radial basis function
- matrix factorization
- missing data
- artificial neural networks
- semi supervised
- singular value decomposition
- basis functions
- high dimensional data
- learning rules
- input output
- visual cortex
- rbf neural network
- training algorithm
- nonlinear systems
- activation function
- high order
- biologically plausible
- back propagation
- learning algorithm
- data sets
- high dimensional
- multilayer perceptron
- latent variables