Alternatives and similar repositories for trieste:

Users that are interested in trieste are comparing it to the libraries listed below

• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆124Updated 4 months ago
• JaxGaussianProcesses / GPJax
  Gaussian processes in JAX.
  ☆477Updated 2 weeks ago
• wesselb / stheno
  Gaussian process modelling in Python
  ☆222Updated 2 months ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆103Updated 3 weeks ago
• google-research / hyperbo
  Pre-trained Gaussian processes for Bayesian optimization
  ☆90Updated 2 months ago
• AaltoML / BayesNewton
  Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
  ☆232Updated last year
• uber-research / TuRBO
  ☆188Updated 6 months ago
• patrick-kidger / optimistix
  Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/
  ☆377Updated this week
• ziatdinovmax / gpax
  Gaussian Processes for Experimental Sciences
  ☆218Updated 3 months ago
• TyXe-BDL / TyXe
  ☆149Updated 2 years ago
• GPflow / GPflowOpt
  Bayesian Optimization using GPflow
  ☆270Updated 4 years ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆431Updated 5 months ago
• dfm / tinygp
  The tiniest of Gaussian Process libraries
  ☆303Updated this week
• alonfnt / bayex
  Minimal Implementation of Bayesian Optimization in JAX
  ☆88Updated last month
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆100Updated last year
• EmuKit / emukit
  A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, exper…
  ☆616Updated last week
• willieneis / bayesian-algorithm-execution
  Bayesian algorithm execution (BAX)
  ☆49Updated 3 years ago
• patrick-kidger / sympy2jax
  Turn SymPy expressions into trainable JAX expressions.
  ☆328Updated 3 weeks ago
• patrick-kidger / sympytorch
  Turning SymPy expressions into PyTorch modules.
  ☆144Updated last year
• google / tree-math
  Mathematical operations for JAX pytrees
  ☆198Updated 2 months ago
• pints-team / pints
  Probabilistic Inference on Noisy Time Series
  ☆231Updated last week
• jax-ml / oryx
  Oryx is a library for probabilistic programming and deep learning built on top of Jax.
  ☆245Updated last week
• google-deepmind / distrax
  ☆548Updated 2 months ago
• facebookresearch / bo_pr
  Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
  ☆72Updated 2 years ago
• jax-ml / bayeux
  State of the art inference for your bayesian models.
  ☆199Updated 2 months ago
• google-deepmind / kfac-jax
  Second Order Optimization and Curvature Estimation with K-FAC in JAX.
  ☆263Updated 2 weeks ago
• probabilistic-numerics / probnum
  Probabilistic Numerics in Python.
  ☆448Updated 9 months ago
• martinjankowiak / saasbo
  SAASBO: a package for high-dimensional bayesian optimization
  ☆41Updated 3 years ago
• patrick-kidger / lineax
  Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax
  ☆413Updated this week
• automl / pybnn
  Bayesian neural network package
  ☆141Updated 3 years ago