Alternatives and similar repositories for COMBO:

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

• facebookresearch / alebo
  Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization
  ☆41Updated 3 years ago
• jungtaekkim / bayeso-benchmarks
  Benchmark functions for Bayesian optimization
  ☆33Updated last year
• rubinxin / CoCaBO_code
  Bayesian Optimisation over Multiple Continuous and Categorical Inputs (CoCaBO)
  ☆51Updated 5 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• ChangYong-Oh / HyperSphere
  ☆16Updated 6 years ago
• zi-w / Ensemble-Bayesian-Optimization
  Code repository for Ensemble Bayesian Optimization
  ☆52Updated 5 years ago
• aryandeshwal / HyBO
  ☆23Updated 2 years ago
• markm541374 / gpbo
  gpbo
  ☆25Updated 4 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆31Updated 3 years ago
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆40Updated 2 years ago
• lfbo-ml / lfbo
  Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022
  ☆44Updated 2 years ago
• ltiao / bore
  Bayesian Optimization with Density-Ratio Estimation
  ☆23Updated 2 years ago
• aminnayebi / HesBO
  The High-dimensional BayesOpt algorithms from "A Framework for Bayesian Optimization in Embedded Subspaces
  ☆41Updated 5 years ago
• kirthevasank / gp-parallel-ts
  Parallelised Thompson Sampling in GPs for Bayesian Optimisation
  ☆36Updated 7 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆49Updated 11 months ago
• facebookresearch / bo_pr
  Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
  ☆72Updated 2 years ago
• j-wilson / MaximizingAcquisitionFunctions
  Code for "Maximizing Acquisition Functions for Bayesian Optimization"
  ☆13Updated 6 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 6 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• misokg / NIPS2017
  Multi-Information Source Optimization
  ☆22Updated 5 years ago
• thjashin / solvegp
  Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)
  ☆22Updated 3 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆21Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• xingchenwan / Casmopolitan
  [ICML'21] Think Global and Act Local: Bayesian Optimisation for Categorical and Mixed Search Spaces
  ☆30Updated 2 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆19Updated 3 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆82Updated 9 months ago
• xinshi-chen / ParticleFlowBayesRule
  Pytorch implementation for "Particle Flow Bayes' Rule"
  ☆14Updated 5 years ago
• kd383 / GPML_SLD
  Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)
  ☆18Updated 7 years ago
• martius-lab / CombOptNet
  Source code for the Paper: CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints}
  ☆72Updated 2 years ago