mgplvm.rdist.GP_circ module

class mgplvm.rdist.GP_circ.GP_circ(manif, m, n_samples, ts, _scale=0.9, ell=None)

Bases: mgplvm.rdist.GPbase.GPbase

I_v(v, sample_idxs=None)

Compute I @ v for some vector v. Here I = S C. v is (n_samples x d x m x n_mc) where n_samples is the number of sample_idxs

property c: torch.Tensor

Return type

Tensor

gmu_parameters()

kl(batch_idxs=None, sample_idxs=None)

Compute KL divergence between prior and posterior. This should be implemented for each class separately

name = 'GP_circ'

property prms

training: bool