Alternatives and similar repositories for bayeso-benchmarks

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

• QUVA-Lab / COMBO
  ☆50Updated last year
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• cambridge-mlg / expressiveness-approx-bnns
  Code for "On the Expressiveness of Approximate Inference in Bayesian Neural Networks"
  ☆13Updated 4 years ago
• lfbo-ml / lfbo
  Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022
  ☆46Updated 3 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 6 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 4 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 4 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆35Updated 4 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆49Updated 10 months ago
• ltiao / bore
  Bayesian Optimization with Density-Ratio Estimation
  ☆24Updated 3 years ago
• franrruiz / uivi
  Code for Unbiased Implicit Variational Inference (UIVI)
  ☆15Updated 6 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• choidami / sst
  ☆50Updated 5 years ago
• rubinxin / CoCaBO_code
  Bayesian Optimisation over Multiple Continuous and Categorical Inputs (CoCaBO)
  ☆52Updated 6 years ago
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆42Updated 3 years ago
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆78Updated last year
• facebookresearch / bo_pr
  Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
  ☆76Updated 3 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆42Updated 5 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• juliagusak / neural-ode-metasolver
  Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561
  ☆25Updated 4 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆93Updated 5 years ago
• qsh-zh / pis
  [ICLR 2022] Path integral sampler
  ☆52Updated 2 years ago
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆29Updated 6 years ago
• siddsax / Normalizing_Flows
  Implementation of Normalizing flows on MNIST https://arxiv.org/abs/1505.05770
  ☆14Updated 7 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 5 years ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆90Updated last year
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆54Updated 5 years ago