Alternatives and similar repositories for GPflowOpt

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

• wujian16 / Cornell-MOE
  A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
  ☆268Updated 5 years ago
• josejimenezluna / pyGPGO
  Bayesian optimization for Python
  ☆246Updated 3 years ago
• automl / RoBO
  RoBO: a Robust Bayesian Optimization framework
  ☆487Updated 6 years ago
• jamesrobertlloyd / gp-structure-search
  ☆238Updated 8 years ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated last year
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆150Updated 6 years ago
• jamesrobertlloyd / gpss-research
  Kernel structure discovery research code - likely to be unstable
  ☆191Updated 10 years ago
• SheffieldML / GPyOpt
  Gaussian Process Optimization using GPy
  ☆947Updated 2 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆234Updated 4 years ago
• rmcantin / bayesopt
  BayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits.
  ☆418Updated 2 years ago
• automl / pybnn
  Bayesian neural network package
  ☆149Updated 4 years ago
• SheffieldML / notebook
  Collection of jupyter notebooks for demonstrating software.
  ☆169Updated 2 years ago
• thuijskens / bayesian-optimization
  Python code for bayesian optimization using Gaussian processes
  ☆312Updated 8 years ago
• sigopt / evalset
  Benchmark suite of test functions suitable for evaluating black-box optimization strategies
  ☆52Updated 3 months ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated last year
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated last year
• mwhoffman / pybo
  Python package for modular Bayesian optimization
  ☆136Updated 4 years ago
• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆114Updated 12 years ago
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆216Updated 6 years ago
• vlad17 / runlmc
  Structurally efficient multi-output linearly coregionalized Gaussian Processes: it's tricky, tricky, tricky, tricky, tricky.
  ☆38Updated 2 years ago
• duvenaud / phd-thesis
  I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth
  ☆185Updated 11 years ago
• kirthevasank / gp-parallel-ts
  Parallelised Thompson Sampling in GPs for Bayesian Optimisation
  ☆36Updated 7 years ago
• pyprob / pyprob
  A probabilistic programming system for simulators and high-performance computing (HPC), based on PyTorch
  ☆389Updated last year
• EmuKit / emukit
  A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, exper…
  ☆632Updated 6 months ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 6 years ago
• baptistar / BOCS
  Bayesian Optimization of Combinatorial Structures
  ☆97Updated 5 years ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 8 years ago
• jmetzen / bayesian_optimization
  Bayesian optimization
  ☆38Updated 5 years ago
• automl / HPOlib1.5
  ☆69Updated 5 years ago
• automl / fanova
  Functional ANOVA
  ☆125Updated 5 months ago