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User Guide
Why tinygp?
Installation Guide
Troubleshooting
Benchmarks
Release Notes
Tutorials
An Introduction to tinygp
Getting Started
Modeling Frameworks
Fitting a Mean Function
Multivariate Data
Custom Kernels
Kernel Transforms
Custom Geometry
Derivative Observations & Pytree Data
Non-Gaussian Likelihoods
Mixture of Kernels
Scalable GPs with Quasiseparable Kernels
Custom Quasiseparable Kernels
Contributor Guide
Code of Conduct
Public API
GaussianProcess
ConditionResult
kernels package
Kernel
Conditioned
Custom
Sum
Product
Constant
DotProduct
Polynomial
Stationary
Exp
ExpSquared
Matern32
Matern52
Cosine
ExpSineSquared
RationalQuadratic
Distance
L1Distance
L2Distance
kernels.quasisep package
Quasisep
Wrapper
Sum
Product
Scale
Celerite
SHO
Exp
Matern32
Matern52
Cosine
CARMA
means package
Mean
Conditioned
noise package
Diagonal
Dense
Banded
solvers package
DirectSolver
QuasisepSolver
solvers.quasisep package
QSM
DiagQSM
StrictLowerTriQSM
StrictUpperTriQSM
LowerTriQSM
UpperTriQSM
SquareQSM
SymmQSM
GeneralQSM
transforms package
Transform
Linear
Cholesky
Subspace
GitHub Repository
Repository
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