Alternatives and similar repositories for AWGF

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

• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆46Updated 2 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆35Updated 3 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆85Updated 5 years ago
• singhalrk / stein_ksd
  ☆10Updated 7 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 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
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆29Updated 6 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆111Updated 3 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆84Updated 6 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated last year
• ChunyuanLI / SVGD
  Tensorflow implementation of Stein Variational Gradient Descent (SVGD)
  ☆26Updated 7 years ago
• tuananhle7 / aesmc
  Library for Auto-Encoding Sequential Monte Carlo
  ☆18Updated last year
• gd-zhang / noisy-K-FAC
  Natural Gradient, Variational Inference
  ☆29Updated 5 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆57Updated last year
• federicobergamin / Variational-Inference-with-Normalizing-Flows
  Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch
  ☆23Updated 5 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆67Updated 6 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• DartML / Stein-Variational-Gradient-Descent
  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
  ☆100Updated 6 years ago
• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆34Updated 2 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 3 years ago
• wgrathwohl / LSD
  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
  ☆49Updated 5 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆53Updated 5 years ago
• dimkal89 / rvae
  ☆37Updated 5 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆42Updated 2 years ago
• thu-ml / fpovi
  Code for "Function Space Particle Optimization for Bayesian Neural Networks"
  ☆18Updated 3 years ago