Alternatives and similar repositories for BBVI

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

• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆85Updated 5 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆39Updated 4 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• EEA-sensors / sequential-parallelization-examples
  This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.
  ☆33Updated 2 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 5 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• brain-research / nngp
  Deep neural network kernel for Gaussian process
  ☆211Updated 5 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• trevorcampbell / bayesian-coresets
  Automated Scalable Bayesian Inference
  ☆130Updated 3 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 4 years ago
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆39Updated 6 years ago
• catniplab / tree_structured_rslds
  Tree-structured recurrent switching linear dynamical systems
  ☆36Updated 5 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• daeilkim / bbvi
  Black Box Variational Inference
  ☆14Updated 10 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• aboustati / vargrad
  Code accompanying VarGrad: A Low-Variance Gradient Estimator for Variational Inference
  ☆12Updated 4 years ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 5 years ago
• JTT94 / filterflow
  Extensible Tensorflow library for differentiable particle filtering. ICML 2021.
  ☆42Updated 2 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆54Updated last year
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆20Updated 3 years ago
• AaltoML / kalman-jax
  Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
  ☆100Updated 2 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆46Updated 7 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 4 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆31Updated 2 years ago