Alternatives and similar repositories for bayeso-benchmarks:

Users that are interested in bayeso-benchmarks are comparing it to the libraries listed below

• lfbo-ml / lfbo
  Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022
  ☆44Updated 2 years ago
• jungtaekkim / bayeso
  Simple, but essential Bayesian optimization package
  ☆94Updated 2 months ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• QUVA-Lab / COMBO
  ☆50Updated 7 months ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• ltiao / bore
  Bayesian Optimization with Density-Ratio Estimation
  ☆23Updated 2 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆82Updated 4 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆47Updated 2 weeks ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆27Updated 7 months ago
• facebookresearch / alebo
  Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization
  ☆41Updated 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
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆31Updated 3 years ago
• changliu00 / AWGF
  Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)
  ☆22Updated 5 years ago
• rubinxin / CoCaBO_code
  Bayesian Optimisation over Multiple Continuous and Categorical Inputs (CoCaBO)
  ☆51Updated 5 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆19Updated 3 years ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆30Updated 3 years ago
• thudzj / ELLA
  Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')
  ☆16Updated 2 years ago
• cambridge-mlg / expressiveness-approx-bnns
  Code for "On the Expressiveness of Approximate Inference in Bayesian Neural Networks"
  ☆13Updated 3 years ago
• facebookresearch / bo_pr
  Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
  ☆72Updated 2 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆27Updated 4 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated 9 months ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 4 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆51Updated 4 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated last year
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆48Updated 10 months ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 3 years ago
• choidami / sst
  ☆49Updated 4 years ago
• jonasrothfuss / meta_learning_pacoh
  Meta-learning Gaussian process (GP) priors via PAC-Bayes bounds
  ☆25Updated last year