Alternatives and similar repositories for csgmcmc:

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

• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆81Updated 4 years ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆111Updated 6 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆81Updated 7 months ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆85Updated 5 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆109Updated 3 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆88Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• damaru2 / ntk
  NTK reading group
  ☆88Updated 5 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆56Updated 3 years ago
• TrentBrick / PyTorchDiscreteFlows
  Discrete Normalizing Flows implemented in PyTorch
  ☆109Updated 3 years ago
• ruosongwang / CNTK
  Convolutional Neural Tangent Kernel
  ☆109Updated 5 years ago
• izmailovpavel / understandingbdl
  ☆236Updated 2 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆48Updated 6 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• g-benton / loss-surface-simplexes
  ☆98Updated 3 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆49Updated 6 years ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆88Updated 9 months ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆145Updated 8 months ago
• google / spectral-density
  Hessian spectral density estimation in TF and Jax
  ☆121Updated 4 years ago
• SamsungLabs / pytorch-ensembles
  Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020
  ☆235Updated 2 years ago
• wiseodd / last_layer_laplace
  Last-layer Laplace approximation code examples
  ☆82Updated 3 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆67Updated 5 years ago
• riannevdberg / sylvester-flows
  ☆178Updated 5 years ago
• team-approx-bayes / dl-with-bayes
  Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"
  ☆244Updated 5 years ago
• PolinaKirichenko / flows_ood
  ☆87Updated 3 years ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆72Updated last year
• MichaelArbel / GeneralizedEBM
  ☆53Updated 6 months ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 4 years ago
• PGM-Lab / probai-2021-pyro
  Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)
  ☆47Updated 3 years ago