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Getting started

  • Installation
  • Design Principles
  • The Sharp Bits
  • New to Gaussian Processes?
  • Introduction to Kernels
  • Regression
  • Classification
  • Count Data Regression
  • Natural Gradients

Accelerating Gaussian processes

  • Sparse Gaussian Process Regression
  • Sparse Stochastic Variational Inference
  • Natural Gradients in Practice
  • Dual Parameterisation of Sparse GPs (t-SVGP)
  • State-Space (Markovian) Gaussian Processes
  • Scalable Multi-Output GPs with OILMM

Applied modelling

  • Gaussian Processes Barycentres
  • Graph Kernels
  • Heteroscedastic Inference
  • Multi-Output Gaussian Processes
  • Orthogonal Additive Kernels
  • Gaussian Processes for Vector Fields and Ocean Current Modelling
  • Spatial Modelling with Composable Gaussian Processes
  • Gridded Data with xarray
  • UCI Data Benchmarking

Guides for customisation

  • Kernel Guide
  • Likelihood Guide
  • Deep Kernel Learning
  • Joint Inference with Numpyro
  • Backend Module Design

Reference

  • API Reference
    • Dataset
    • xarray
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    • Mean Functions
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Migrations

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Project

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  • GPJax Governance Document
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On this page

  • SumMeanFunction
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  4. SumMeanFunction
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SumMeanFunction#

class gpjax.mean_functions.SumMeanFunction(means)[source]#

Bases: CombinationMeanFunction

Sum of mean functions.

Parameters:

means (list)

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