trieste

The library root. See bayesian_optimizer for the core optimizer, which requires models (see models), and data sets (see data). The acquisition package provides a selection of acquisition algorithms and the functionality to define your own. The ask_tell_optimization package provides API for Ask-Tell optimization and manual control of the optimization loop. The objectives package contains several popular objective functions, useful for experimentation.

Subpackages

• trieste.acquisition
  • trieste.acquisition.function
    • trieste.acquisition.function.active_learning
    • trieste.acquisition.function.continuous_thompson_sampling
    • trieste.acquisition.function.entropy
    • trieste.acquisition.function.function
    • trieste.acquisition.function.greedy_batch
    • trieste.acquisition.function.multi_objective
    • trieste.acquisition.function.utils
  • trieste.acquisition.multi_objective
    • trieste.acquisition.multi_objective.dominance
    • trieste.acquisition.multi_objective.pareto
    • trieste.acquisition.multi_objective.partition
  • trieste.acquisition.interface
  • trieste.acquisition.optimizer
  • trieste.acquisition.rule
  • trieste.acquisition.sampler
• trieste.models
  • trieste.models.gpflow
    • trieste.models.gpflow.builders
    • trieste.models.gpflow.inducing_point_selectors
    • trieste.models.gpflow.optimizer
    • trieste.models.gpflow.sampler
  • trieste.models.gpflux
    • trieste.models.gpflux.builders
  • trieste.models.keras
    • trieste.models.keras.architectures
    • trieste.models.keras.builders
    • trieste.models.keras.sampler
  • trieste.models.optimizer
  • trieste.models.utils
• trieste.objectives
  • trieste.objectives.multi_objectives
  • trieste.objectives.multifidelity_objectives
  • trieste.objectives.single_objectives
  • trieste.objectives.utils
• trieste.utils

Submodules

• trieste.ask_tell_optimization
• trieste.bayesian_optimizer
• trieste.data
• trieste.logging
• trieste.observer
• trieste.space
• trieste.types
• trieste.version