Alternatives and similar repositories for add-gp-bandits

Users that are interested in add-gp-bandits are comparing it to the libraries listed below

• zi-w / Max-value-Entropy-Search
  Max-value Entropy Search for Efficient Bayesian Optimization
  ☆76Updated 3 years ago
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆32Updated 8 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 8 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 3 years ago
• zi-w / Structural-Kernel-Learning-for-HDBBO
  Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
  ☆14Updated 6 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• kirthevasank / mf-gp-ucb
  Multi-fidelity Gaussian Process Bandit Optimisation
  ☆39Updated 8 years ago
• aminnayebi / HesBO
  The High-dimensional BayesOpt algorithms from "A Framework for Bayesian Optimization in Embedded Subspaces
  ☆41Updated 6 years ago
• RaulAstudillo06 / BOCF
  A framework for Bayesian optimization of composite functions.
  ☆14Updated 2 years ago
• ebonilla / mtgp
  Multi-task Gaussian Process
  ☆43Updated 10 years ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 8 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆114Updated 11 years ago
• zi-w / GP-EST
  Bayesian optimization with the Gaussian process assumption
  ☆30Updated 9 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• zi-w / Ensemble-Bayesian-Optimization
  Code repository for Ensemble Bayesian Optimization
  ☆53Updated 5 years ago
• kirthevasank / gp-parallel-ts
  Parallelised Thompson Sampling in GPs for Bayesian Optimisation
  ☆36Updated 7 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆150Updated 6 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆24Updated 9 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 8 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 years ago
• ChunyuanLI / pSGLD
  AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)
  ☆35Updated 6 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• MethodsOfMachineLearning / entropy-search
  Entropy Search for Information-Efficient Global Optimization - JMLR v13
  ☆29Updated 8 years ago
• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆93Updated 7 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• aboustati / dgplib
  Library for Deep Gaussian Processes based on GPflow
  ☆19Updated 5 years ago