Alternatives and similar repositories for bayesian_benchmarks:

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

• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆41Updated 8 months ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆31Updated 3 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• frgsimpson / kitt
  Kernel Identification Through Transformers
  ☆12Updated last year
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆30Updated 8 months ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆19Updated 3 years ago
• shalijiang / bo
  code for BINOCULARS and Multi-Step BO
  ☆11Updated 4 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• vr308 / GPLVM
  Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch
  ☆15Updated 3 years ago
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆21Updated 4 years ago
• wjmaddox / online_vargp
  Online variational GPs
  ☆32Updated last year
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 5 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• facebookresearch / ContextualBO
  Code associated with paper "High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization"
  ☆15Updated 4 years ago
• ntienvu / KnownOptimum_BO
  Release code for ICML2020 Knowing The What But Not The Where in Bayesian Optimization
  ☆15Updated 2 years ago
• ltiao / bore
  Bayesian Optimization with Density-Ratio Estimation
  ☆23Updated 2 years ago
• spbu-math-cs / Riemannian-Gaussian-Processes
  Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".
  ☆28Updated last month
• mstaib / mmd-dro-code
  Accompanying code for our NeurIPS 2019 paper
  ☆12Updated 5 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 years ago
• EEA-sensors / sequential-parallelization-examples
  This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.
  ☆31Updated last year
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 5 years ago
• trappmartin / DeepStructuredMixtures
  Code for Deep Structured Mixtures of Gaussian Processes (DSMGPs)
  ☆11Updated 3 years ago
• ratschlab / repulsive_ensembles
  Repo for our paper "Repulsive deep ensembles are Bayesian"
  ☆19Updated 3 years ago
• ntienvu / MiniBO
  Mini Bayesian Optimization package for ACML2020 Tutorial on Bayesian Optimization
  ☆15Updated 2 years ago
• karlnapf / kernel_exp_family
  Various estimators of the infinite dimensional exponential family model
  ☆15Updated 7 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated 9 months ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆25Updated 5 years ago