## doc: kernel_se

Squared exponential covariance function

### Syntax

K = kernel_se(X,'diag',s,ells)
K = kernel_se(X,Y,s,ells)

### Arguments

*X* matrix *(nx, d)* where *nx* is the number of data points and *d* is the dimension*Y* matrix *(ny, d)* or 'diag' for diagonal self covariance*s* scalar *(1,1)* for covariance scale*ell* vector *(1,d)* for covariance length-scales

### Outputs

*K* matrix *(nx, ny)* or diagonal *(nx, 1)*

### See also

kernel_matern | kernel_se