mGPLVM
Getting Started
Install
Examples
(Bayesian) GPFA
Supervised learning and decoding with manifold GPLVMs
Applying mGPLVM to synthetic neural data generated from circular latents
API
mgplvm package
Subpackages
mgplvm.crossval package
mgplvm.fast_utils package
mgplvm.kernels package
mgplvm.lpriors package
mgplvm.manifolds package
mgplvm.models package
Submodules
Module contents
mgplvm.optimisers package
mgplvm.rdist package
mgplvm.syndata package
Submodules
Module contents
mGPLVM
»
mgplvm package
»
mgplvm.models package
»
mgplvm.models.svgplvm module
View page source
mgplvm.models.svgplvm module
class
mgplvm.models.svgplvm.
SvgpLvm
(
n
,
m
,
n_samples
,
z
,
kernel
,
likelihood
,
lat_dist
,
lprior
,
whiten
=
True
,
tied_samples
=
True
)
[source]
Bases:
mgplvm.models.gplvm.Gplvm
name
=
'Svgplvm'
training
:
bool