Welcome to ESEm’s documentation!¶

Contents:

  • Installing ESEm
    • Using PyPi
    • Using conda
    • Dependencies
  • What’s new in ESEm
    • What’s new in ESEm 1.1
  • Emulating with ESEm
    • Gaussian processes emulation
    • Neural network emulation
    • Random forest emulation
    • Data processing
    • Feature selection
  • Calibrating with ESEm
    • Using approximate Bayesian computation (ABC)
    • Using Markov-chain Monte-Carlo
  • Examples
    • Emulating using GPs
    • Emulating using CNNs
    • Random Forest Example: Cloud-resolving model sensitivity
    • Calibrating GPs using ABC
    • Calibrating GPs using MCMC
    • CMIP6 Emulation
    • Create paper emulation figure
  • API reference
    • Top-level functions
    • Emulator
    • Sampler
    • Wrappers
    • ModelAdaptor
    • DataProcessor
    • Utilities
  • ESEm design
    • Emulation
    • Calibration
  • Glossary

Indices and tables¶

  • Index

  • Module Index

  • Search Page

esem

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Contents:

  • Installing ESEm
  • What’s new in ESEm
  • Emulating with ESEm
  • Calibrating with ESEm
  • Examples
  • API reference
  • ESEm design
  • Glossary

Related Topics

  • Documentation overview
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